nicolauduran45/climate-science-reranker

README.md

@@ -1,3 +1,866 @@
----
-license: apache-2.0
----
+---
+language:
+- en
+license: apache-2.0
+tags:
+- sentence-transformers
+- cross-encoder
+- generated_from_trainer
+- dataset_size:263476
+- loss:BinaryCrossEntropyLoss
+base_model: cross-encoder/ms-marco-MiniLM-L6-v2
+pipeline_tag: text-ranking
+library_name: sentence-transformers
+metrics:
+- map
+- mrr@10
+- ndcg@10
+model-index:
+- name: Climate-Science-Reranker
+  results:
+  - task:
+      type: cross-encoder-reranking
+      name: Cross Encoder Reranking
+    dataset:
+      name: climate science eval
+      type: climate-science-eval
+    metrics:
+    - type: map
+      value: 0.6629
+      name: Map
+    - type: mrr@10
+      value: 0.6554
+      name: Mrr@10
+    - type: ndcg@10
+      value: 0.7068
+      name: Ndcg@10
+---
+
+# Climate-Science-Reranker
+
+This is a [Cross Encoder](https://www.sbert.net/docs/cross_encoder/usage/usage.html) model finetuned from [cross-encoder/ms-marco-MiniLM-L6-v2](https://huggingface.co/cross-encoder/ms-marco-MiniLM-L6-v2) using the [sentence-transformers](https://www.SBERT.net) library. It computes scores for pairs of texts, which can be used for text reranking and semantic search.
+
+## Model Details
+
+### Model Description
+- **Model Type:** Cross Encoder
+- **Base model:** [cross-encoder/ms-marco-MiniLM-L6-v2](https://huggingface.co/cross-encoder/ms-marco-MiniLM-L6-v2) <!-- at revision ce0834f22110de6d9222af7a7a03628121708969 -->
+- **Maximum Sequence Length:** 512 tokens
+- **Number of Output Labels:** 1 label
+<!-- - **Training Dataset:** Unknown -->
+- **Language:** en
+- **License:** apache-2.0
+
+### Model Sources
+
+- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
+- **Documentation:** [Cross Encoder Documentation](https://www.sbert.net/docs/cross_encoder/usage/usage.html)
+- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
+- **Hugging Face:** [Cross Encoders on Hugging Face](https://huggingface.co/models?library=sentence-transformers&other=cross-encoder)
+
+## Usage
+
+### Direct Usage (Sentence Transformers)
+
+First install the Sentence Transformers library:
+
+```bash
+pip install -U sentence-transformers
+```
+
+Then you can load this model and run inference.
+```python
+from sentence_transformers import CrossEncoder
+
+# Download from the 🤗 Hub
+model = CrossEncoder("cross_encoder_model_id")
+# Get scores for pairs of texts
+pairs = [
+    ["The researchers say that with the right design a Mersey barrage has the potential to become a globally identifiable piece of architectural infrastructure - a 'hydropower landmark' boosting tourism to the region.", 'Currently there is renewed interest in harnessing the vast tidal resource to combat the twin challenges of climate change and energy security. However, within the UK no tidal barrage proposals have passed the development stage, this is due to a combination of high cost and environmental concerns. This paper demonstrates how a framework, such as the North West Hydro Resource Model can be applied to tidal barrages, with the Mersey barrage as a case study. The model materialised in order to provide developers with a tool to successfully identify the capacity of hydropower schemes in a specific location. A key feature of the resource model is the understanding that there is no single barrier to the utilisation of small hydropower but several obstacles, which together impede development. Thus, this paper contributes in part to a fully holistic treatment of tidal barrages, recognising that apart from energy generation, other environmental, societal and economic opportunities arise and must be fully investigated for robust decision-making. This study demonstrates how considering the societal needs of the people and the necessity for compensatory habitats, for example, an organic architectural design has developed, which aims to enhance rather than detract from the Mersey.'],
+    ["The researchers say that with the right design a Mersey barrage has the potential to become a globally identifiable piece of architectural infrastructure - a 'hydropower landmark' boosting tourism to the region.", 'Rainbows contribute to human wellbeing by providing an inspiring connection to nature. Because the rainbow is an atmospheric optical phenomenon that results from the refraction of sunlight by rainwater droplets, changes in precipitation and cloud cover due to anthropogenic climate forcing will alter rainbow distribution. Yet, we lack a basic understanding of the current spatial distribution of rainbows and how climate change might alter this pattern. To assess how climate change might affect rainbow viewing opportunities, we developed a global database of crowd-sourced photographed rainbows, trained an empirical model of rainbow occurrence, and applied this model to present-day climate and three future climate scenarios. Results suggest that the average terrestrial location on Earth currently has 117 ± 71 days per year with conditions suitable for rainbows. By 2100, climate change is likely to generate a 4.0–4.9 % net increase in mean global annual rainbow-days (i.e., days with at least one rainbow), with the greatest change under the highest emission scenario. Around 21–34 % of land areas will lose rainbow-days and 66–79 % will gain rainbow-days, with rainbow gain hotspots mainly in high-latitude and high-elevation regions with smaller human populations. Our research demonstrates that alterations to non-tangible environmental attributes due to climate change could be significant and are worthy of consideration and mitigation.'],
+    ["The researchers say that with the right design a Mersey barrage has the potential to become a globally identifiable piece of architectural infrastructure - a 'hydropower landmark' boosting tourism to the region.", 'The ascendancy of dinosaurs to become dominant components of terrestrial ecosystems was a pivotal event in the history of life, yet the drivers of their early evolution and biodiversity are poorly understood.1Brusatte S.L. Benton M.J. Ruta M. Lloyd G.T. The first 50 Myr of dinosaur evolution: macroevolutionary pattern and morphological disparity.Biol. Lett. 2008; 4: 733-736https://doi.org/10.1098/rsbl.2008.0441Crossref PubMed Scopus (105) Google Scholar,2Irmis R.B. Evaluating hypotheses for the early diversification of dinosaurs.Earth Environ. Sci. Trans. R. Soc. Edinb. 2010; 101: 397-426https://doi.org/10.1017/S1755691011020068Crossref Scopus (94) Google Scholar,3Benton M.J. Forth J. Langer M.C. Models for the rise of the dinosaurs.Curr. Biol. 2014; 24: R87-R95https://doi.org/10.1016/j.cub.2013.11.063Abstract Full Text Full Text PDF PubMed Scopus (93) Google Scholar During their early diversification in the Late Triassic, dinosaurs were initially rare and geographically restricted, only attaining wider distributions and greater abundance following the end-Triassic mass extinction event.4Brusatte S.L. Benton M.J. Ruta M. Lloyd G.T. Superiority, competition, and opportunism in the evolutionary radiation of dinosaurs.Science. 2008; 321: 1485-1488https://doi.org/10.1126/science.1161833Crossref PubMed Scopus (334) Google Scholar,5Langer M.C. Ezcurra M.D. Bittencourt J.S. Novas F.E. The origin and early evolution of dinosaurs.Biol. Rev. Camb. Philos. Soc. 2010; 85: 55-110https://doi.org/10.1111/j.1469-185X.2009.00094.xCrossref PubMed Scopus (212) Google Scholar,6Langer M.C. Godoy P.L. So volcanoes created the dinosaurs? a quantitative characterization of the early evolution of terrestrial pan-aves.Front. Earth Sci. 2022; 10https://doi.org/10.3389/feart.2022.899562Crossref PubMed Scopus (3) Google Scholar This pattern is consistent with an opportunistic expansion model, initiated by the extinction of co-occurring groups such as aetosaurs, rauisuchians, and therapsids.4Brusatte S.L. Benton M.J. Ruta M. Lloyd G.T. Superiority, competition, and opportunism in the evolutionary radiation of dinosaurs.Science. 2008; 321: 1485-1488https://doi.org/10.1126/science.1161833Crossref PubMed Scopus (334) Google Scholar,7Tucker M.E. Benton M.J. Triassic environments, climates and reptile evolution.Palaeogeogr. Palaeoclimatol. Palaeoecol. 1982; 40: 361-379https://doi.org/10.1016/0031-0182(82)90034-7Crossref Scopus (89) Google Scholar,8Benton M.J. Dinosaur success in the triassic: a noncompetitive ecological model.Q. Rev. Biol. 1983; 58: 29-55Crossref Scopus (170) Google Scholar However, this pattern could instead be a response to changes in global climatic distributions through the Triassic to Jurassic transition, especially given the increasing evidence that climate played a key role in constraining Triassic dinosaur distributions.7Tucker M.E. Benton M.J. Triassic environments, climates and reptile evolution.Palaeogeogr. Palaeoclimatol. Palaeoecol. 1982; 40: 361-379https://doi.org/10.1016/0031-0182(82)90034-7Crossref Scopus (89) Google Scholar,9Whiteside J.H. Lindström S. Irmis R.B. Glasspool I.J. Schaller M.F. Dunlavey M. Nesbitt S.J. Smith N.D. Turner A.H. Extreme ecosystem instability suppressed tropical dinosaur dominance for 30 million years.Proc. Natl. Acad. Sci. USA. 2015; 112: 7909-7913https://doi.org/10.1073/pnas.1505252112Crossref PubMed Scopus (61) Google Scholar,10Bernardi M. Gianolla P. Petti F.M. Mietto P. Benton M.J. Dinosaur diversification linked with the Carnian pluvial episode.Nat. Commun. 2018; 9: 1499https://doi.org/10.1038/s41467-018-03996-1Crossref PubMed Scopus (87) Google Scholar,11Lovelace D.M. Hartman S.A. Mathewson P.D. Linzmeier B.J. Porter W.P. Modeling Dragons: using linked mechanistic physiological and microclimate models to explore environmental, physiological, and morphological constraints on the early evolution of dinosaurs.PLoS One. 2020; 15e0223872https://doi.org/10.1371/journal.pone.0223872Crossref Scopus (8) Google Scholar,12Mancuso A.C. Benavente C.A. Irmis R.B. Mundil R. Evidence for the Carnian pluvial episode in Gondwana: new multiproxy climate records and their bearing on early dinosaur diversification.Gondwana Res. 2020; 86: 104-125https://doi.org/10.1016/j.gr.2020.05.009Crossref Scopus (35) Google Scholar,13Mancuso A.C. Irmis R.B. Pedernera T.E. Gaetano L.C. Benavente C.A. Breeden III B.T. Paleoenvironmental and biotic changes in the late triassic of Argentina: testing hypotheses of abiotic forcing at the basin scale.Front. Earth Sci. 2022; 10https://doi.org/10.3389/feart.2022.883788Crossref PubMed Scopus (4) Google Scholar,14Kent D.V. Clemmensen L.B. Northward dispersal of dinosaurs from Gondwana to Greenland at the mid-Norian (215–212 Ma, Late Triassic) dip in atmospheric pCO2.Proc. Natl. Acad. Sci. USA. 2021; 118e2020778118https://doi.org/10.1073/pnas.2020778118Crossref Scopus (16) Google Scholar,15Griffin C.T. Wynd B.M. Munyikwa D. Broderick T.J. Zondo M. Tolan S. Langer M.C. Nesbitt S.J. Taruvinga H.R. Africa\'s oldest dinosaurs reveal early suppression of dinosaur distribution.Nature. 2022; 609: 313-319https://doi.org/10.1038/s41586-022-05133-xCrossref PubMed Scopus (4) Google Scholar,16Olsen P. Sha J. Fang Y. Chang C. Whiteside J.H. Kinney S. Sues H.-D. Kent D. Schaller M. Vajda V. Arctic ice and the ecological rise of the dinosaurs.Sci. Adv. 2022; 8eabo6342https://doi.org/10.1126/sciadv.abo6342Crossref Scopus (5) Google Scholar Here, we test this hypothesis and elucidate how climate influenced early dinosaur distribution by quantitatively examining changes in dinosaur and tetrapod "climatic niche space" across the Triassic-Jurassic boundary. Statistical analyses show that Late Triassic sauropodomorph dinosaurs occupied a more restricted climatic niche space than other tetrapods and dinosaurs, being excluded from the hottest, low-latitude climate zones. A subsequent, earliest Jurassic expansion of sauropodomorph geographic distribution is linked to the expansion of their preferred climatic conditions. Evolutionary model-fitting analyses provide evidence for an important evolutionary shift from cooler to warmer climatic niches during the origin of Sauropoda. These results are consistent with the hypothesis that global abundance of sauropodomorph dinosaurs was facilitated by climatic change and provide support for the key role of climate in the ascendancy of dinosaurs.'],
+    ["The researchers say that with the right design a Mersey barrage has the potential to become a globally identifiable piece of architectural infrastructure - a 'hydropower landmark' boosting tourism to the region.", 'The development of technologies to slow climate change has been identified as a global imperative. Nonetheless, such ‘green’ technologies can potentially have negative impacts on biodiversity. We explored how climate change and the mining of lithium for green technologies influence surface water availability, primary productivity and the abundance of three threatened and economically important flamingo species in the ‘Lithium Triangle’ of the Chilean Andes. We combined climate and primary productivity data with remotely sensed measures of surface water levels and a 30-year dataset on flamingo abundance using structural equation modelling. We found that, regionally, flamingo abundance fluctuated dramatically from year-to-year in response to variation in surface water levels and primary productivity but did not exhibit any temporal trends. Locally, in the Salar de Atacama—where lithium mining is focused—we found that mining was negatively correlated with the abundance of two of the three flamingo species. These results suggest continued increases in lithium mining and declines in surface water could soon have dramatic effects on flamingo abundance across their range. Efforts to slow the expansion of mining and the impacts of climate change are, therefore, urgently needed to benefit local biodiversity and the local human economy that depends on it.'],
+    ["The researchers say that with the right design a Mersey barrage has the potential to become a globally identifiable piece of architectural infrastructure - a 'hydropower landmark' boosting tourism to the region.", 'Rivers can abruptly shift pathways in rare events called avulsions, which cause devastating floods. The controls on avulsion locations are poorly understood as a result of sparse data on such features. We analyzed nearly 50 years of satellite imagery and documented 113 avulsions across the globe that indicate three distinct controls on avulsion location. Avulsions on fans coincide with valley-confinement change, whereas avulsions on deltas are primarily clustered within the backwater zone, indicating a control by spatial flow deceleration or acceleration during floods. However, 38% of avulsions on deltas occurred upstream of backwater effects. These events occurred in steep, sediment-rich rivers in tropical and desert environments. Our results indicate that avulsion location on deltas is set by the upstream extent of flood-driven erosion, which is typically limited to the backwater zone but can extend far upstream in steep, sediment-laden rivers. Our findings elucidate how avulsion hazards might respond to land use and climate change.'],
+]
+scores = model.predict(pairs)
+print(scores.shape)
+# (5,)
+
+# Or rank different texts based on similarity to a single text
+ranks = model.rank(
+    "The researchers say that with the right design a Mersey barrage has the potential to become a globally identifiable piece of architectural infrastructure - a 'hydropower landmark' boosting tourism to the region.",
+    [
+        'Currently there is renewed interest in harnessing the vast tidal resource to combat the twin challenges of climate change and energy security. However, within the UK no tidal barrage proposals have passed the development stage, this is due to a combination of high cost and environmental concerns. This paper demonstrates how a framework, such as the North West Hydro Resource Model can be applied to tidal barrages, with the Mersey barrage as a case study. The model materialised in order to provide developers with a tool to successfully identify the capacity of hydropower schemes in a specific location. A key feature of the resource model is the understanding that there is no single barrier to the utilisation of small hydropower but several obstacles, which together impede development. Thus, this paper contributes in part to a fully holistic treatment of tidal barrages, recognising that apart from energy generation, other environmental, societal and economic opportunities arise and must be fully investigated for robust decision-making. This study demonstrates how considering the societal needs of the people and the necessity for compensatory habitats, for example, an organic architectural design has developed, which aims to enhance rather than detract from the Mersey.',
+        'Rainbows contribute to human wellbeing by providing an inspiring connection to nature. Because the rainbow is an atmospheric optical phenomenon that results from the refraction of sunlight by rainwater droplets, changes in precipitation and cloud cover due to anthropogenic climate forcing will alter rainbow distribution. Yet, we lack a basic understanding of the current spatial distribution of rainbows and how climate change might alter this pattern. To assess how climate change might affect rainbow viewing opportunities, we developed a global database of crowd-sourced photographed rainbows, trained an empirical model of rainbow occurrence, and applied this model to present-day climate and three future climate scenarios. Results suggest that the average terrestrial location on Earth currently has 117 ± 71 days per year with conditions suitable for rainbows. By 2100, climate change is likely to generate a 4.0–4.9 % net increase in mean global annual rainbow-days (i.e., days with at least one rainbow), with the greatest change under the highest emission scenario. Around 21–34 % of land areas will lose rainbow-days and 66–79 % will gain rainbow-days, with rainbow gain hotspots mainly in high-latitude and high-elevation regions with smaller human populations. Our research demonstrates that alterations to non-tangible environmental attributes due to climate change could be significant and are worthy of consideration and mitigation.',
+        'The ascendancy of dinosaurs to become dominant components of terrestrial ecosystems was a pivotal event in the history of life, yet the drivers of their early evolution and biodiversity are poorly understood.1Brusatte S.L. Benton M.J. Ruta M. Lloyd G.T. The first 50 Myr of dinosaur evolution: macroevolutionary pattern and morphological disparity.Biol. Lett. 2008; 4: 733-736https://doi.org/10.1098/rsbl.2008.0441Crossref PubMed Scopus (105) Google Scholar,2Irmis R.B. Evaluating hypotheses for the early diversification of dinosaurs.Earth Environ. Sci. Trans. R. Soc. Edinb. 2010; 101: 397-426https://doi.org/10.1017/S1755691011020068Crossref Scopus (94) Google Scholar,3Benton M.J. Forth J. Langer M.C. Models for the rise of the dinosaurs.Curr. Biol. 2014; 24: R87-R95https://doi.org/10.1016/j.cub.2013.11.063Abstract Full Text Full Text PDF PubMed Scopus (93) Google Scholar During their early diversification in the Late Triassic, dinosaurs were initially rare and geographically restricted, only attaining wider distributions and greater abundance following the end-Triassic mass extinction event.4Brusatte S.L. Benton M.J. Ruta M. Lloyd G.T. Superiority, competition, and opportunism in the evolutionary radiation of dinosaurs.Science. 2008; 321: 1485-1488https://doi.org/10.1126/science.1161833Crossref PubMed Scopus (334) Google Scholar,5Langer M.C. Ezcurra M.D. Bittencourt J.S. Novas F.E. The origin and early evolution of dinosaurs.Biol. Rev. Camb. Philos. Soc. 2010; 85: 55-110https://doi.org/10.1111/j.1469-185X.2009.00094.xCrossref PubMed Scopus (212) Google Scholar,6Langer M.C. Godoy P.L. So volcanoes created the dinosaurs? a quantitative characterization of the early evolution of terrestrial pan-aves.Front. Earth Sci. 2022; 10https://doi.org/10.3389/feart.2022.899562Crossref PubMed Scopus (3) Google Scholar This pattern is consistent with an opportunistic expansion model, initiated by the extinction of co-occurring groups such as aetosaurs, rauisuchians, and therapsids.4Brusatte S.L. Benton M.J. Ruta M. Lloyd G.T. Superiority, competition, and opportunism in the evolutionary radiation of dinosaurs.Science. 2008; 321: 1485-1488https://doi.org/10.1126/science.1161833Crossref PubMed Scopus (334) Google Scholar,7Tucker M.E. Benton M.J. Triassic environments, climates and reptile evolution.Palaeogeogr. Palaeoclimatol. Palaeoecol. 1982; 40: 361-379https://doi.org/10.1016/0031-0182(82)90034-7Crossref Scopus (89) Google Scholar,8Benton M.J. Dinosaur success in the triassic: a noncompetitive ecological model.Q. Rev. Biol. 1983; 58: 29-55Crossref Scopus (170) Google Scholar However, this pattern could instead be a response to changes in global climatic distributions through the Triassic to Jurassic transition, especially given the increasing evidence that climate played a key role in constraining Triassic dinosaur distributions.7Tucker M.E. Benton M.J. Triassic environments, climates and reptile evolution.Palaeogeogr. Palaeoclimatol. Palaeoecol. 1982; 40: 361-379https://doi.org/10.1016/0031-0182(82)90034-7Crossref Scopus (89) Google Scholar,9Whiteside J.H. Lindström S. Irmis R.B. Glasspool I.J. Schaller M.F. Dunlavey M. Nesbitt S.J. Smith N.D. Turner A.H. Extreme ecosystem instability suppressed tropical dinosaur dominance for 30 million years.Proc. Natl. Acad. Sci. USA. 2015; 112: 7909-7913https://doi.org/10.1073/pnas.1505252112Crossref PubMed Scopus (61) Google Scholar,10Bernardi M. Gianolla P. Petti F.M. Mietto P. Benton M.J. Dinosaur diversification linked with the Carnian pluvial episode.Nat. Commun. 2018; 9: 1499https://doi.org/10.1038/s41467-018-03996-1Crossref PubMed Scopus (87) Google Scholar,11Lovelace D.M. Hartman S.A. Mathewson P.D. Linzmeier B.J. Porter W.P. Modeling Dragons: using linked mechanistic physiological and microclimate models to explore environmental, physiological, and morphological constraints on the early evolution of dinosaurs.PLoS One. 2020; 15e0223872https://doi.org/10.1371/journal.pone.0223872Crossref Scopus (8) Google Scholar,12Mancuso A.C. Benavente C.A. Irmis R.B. Mundil R. Evidence for the Carnian pluvial episode in Gondwana: new multiproxy climate records and their bearing on early dinosaur diversification.Gondwana Res. 2020; 86: 104-125https://doi.org/10.1016/j.gr.2020.05.009Crossref Scopus (35) Google Scholar,13Mancuso A.C. Irmis R.B. Pedernera T.E. Gaetano L.C. Benavente C.A. Breeden III B.T. Paleoenvironmental and biotic changes in the late triassic of Argentina: testing hypotheses of abiotic forcing at the basin scale.Front. Earth Sci. 2022; 10https://doi.org/10.3389/feart.2022.883788Crossref PubMed Scopus (4) Google Scholar,14Kent D.V. Clemmensen L.B. Northward dispersal of dinosaurs from Gondwana to Greenland at the mid-Norian (215–212 Ma, Late Triassic) dip in atmospheric pCO2.Proc. Natl. Acad. Sci. USA. 2021; 118e2020778118https://doi.org/10.1073/pnas.2020778118Crossref Scopus (16) Google Scholar,15Griffin C.T. Wynd B.M. Munyikwa D. Broderick T.J. Zondo M. Tolan S. Langer M.C. Nesbitt S.J. Taruvinga H.R. Africa\'s oldest dinosaurs reveal early suppression of dinosaur distribution.Nature. 2022; 609: 313-319https://doi.org/10.1038/s41586-022-05133-xCrossref PubMed Scopus (4) Google Scholar,16Olsen P. Sha J. Fang Y. Chang C. Whiteside J.H. Kinney S. Sues H.-D. Kent D. Schaller M. Vajda V. Arctic ice and the ecological rise of the dinosaurs.Sci. Adv. 2022; 8eabo6342https://doi.org/10.1126/sciadv.abo6342Crossref Scopus (5) Google Scholar Here, we test this hypothesis and elucidate how climate influenced early dinosaur distribution by quantitatively examining changes in dinosaur and tetrapod "climatic niche space" across the Triassic-Jurassic boundary. Statistical analyses show that Late Triassic sauropodomorph dinosaurs occupied a more restricted climatic niche space than other tetrapods and dinosaurs, being excluded from the hottest, low-latitude climate zones. A subsequent, earliest Jurassic expansion of sauropodomorph geographic distribution is linked to the expansion of their preferred climatic conditions. Evolutionary model-fitting analyses provide evidence for an important evolutionary shift from cooler to warmer climatic niches during the origin of Sauropoda. These results are consistent with the hypothesis that global abundance of sauropodomorph dinosaurs was facilitated by climatic change and provide support for the key role of climate in the ascendancy of dinosaurs.',
+        'The development of technologies to slow climate change has been identified as a global imperative. Nonetheless, such ‘green’ technologies can potentially have negative impacts on biodiversity. We explored how climate change and the mining of lithium for green technologies influence surface water availability, primary productivity and the abundance of three threatened and economically important flamingo species in the ‘Lithium Triangle’ of the Chilean Andes. We combined climate and primary productivity data with remotely sensed measures of surface water levels and a 30-year dataset on flamingo abundance using structural equation modelling. We found that, regionally, flamingo abundance fluctuated dramatically from year-to-year in response to variation in surface water levels and primary productivity but did not exhibit any temporal trends. Locally, in the Salar de Atacama—where lithium mining is focused—we found that mining was negatively correlated with the abundance of two of the three flamingo species. These results suggest continued increases in lithium mining and declines in surface water could soon have dramatic effects on flamingo abundance across their range. Efforts to slow the expansion of mining and the impacts of climate change are, therefore, urgently needed to benefit local biodiversity and the local human economy that depends on it.',
+        'Rivers can abruptly shift pathways in rare events called avulsions, which cause devastating floods. The controls on avulsion locations are poorly understood as a result of sparse data on such features. We analyzed nearly 50 years of satellite imagery and documented 113 avulsions across the globe that indicate three distinct controls on avulsion location. Avulsions on fans coincide with valley-confinement change, whereas avulsions on deltas are primarily clustered within the backwater zone, indicating a control by spatial flow deceleration or acceleration during floods. However, 38% of avulsions on deltas occurred upstream of backwater effects. These events occurred in steep, sediment-rich rivers in tropical and desert environments. Our results indicate that avulsion location on deltas is set by the upstream extent of flood-driven erosion, which is typically limited to the backwater zone but can extend far upstream in steep, sediment-laden rivers. Our findings elucidate how avulsion hazards might respond to land use and climate change.',
+    ]
+)
+# [{'corpus_id': ..., 'score': ...}, {'corpus_id': ..., 'score': ...}, ...]
+```
+
+<!--
+### Direct Usage (Transformers)
+
+<details><summary>Click to see the direct usage in Transformers</summary>
+
+</details>
+-->
+
+<!--
+### Downstream Usage (Sentence Transformers)
+
+You can finetune this model on your own dataset.
+
+<details><summary>Click to expand</summary>
+
+</details>
+-->
+
+<!--
+### Out-of-Scope Use
+
+*List how the model may foreseeably be misused and address what users ought not to do with the model.*
+-->
+
+## Evaluation
+
+### Metrics
+
+#### Cross Encoder Reranking
+
+* Dataset: `climate-science-eval`
+* Evaluated with [<code>CrossEncoderRerankingEvaluator</code>](https://sbert.net/docs/package_reference/cross_encoder/evaluation.html#sentence_transformers.cross_encoder.evaluation.CrossEncoderRerankingEvaluator) with these parameters:
+  ```json
+  {
+      "at_k": 10,
+      "always_rerank_positives": true
+  }
+  ```
+
+| Metric      | Value                |
+|:------------|:---------------------|
+| map         | 0.6629 (+0.4483)     |
+| mrr@10      | 0.6554 (+0.4475)     |
+| **ndcg@10** | **0.7068 (+0.4669)** |
+
+<!--
+## Bias, Risks and Limitations
+
+*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
+-->
+
+<!--
+### Recommendations
+
+*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
+-->
+
+## Training Details
+
+### Training Dataset
+
+#### Unnamed Dataset
+
+* Size: 263,476 training samples
+* Columns: <code>query</code>, <code>answer</code>, and <code>label</code>
+* Approximate statistics based on the first 1000 samples:
+  |         | query                                                                                            | answer                                                                                              | label                                           |
+  |:--------|:-------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------|:------------------------------------------------|
+  | type    | string                                                                                           | string                                                                                              | int                                             |
+  | details | <ul><li>min: 55 characters</li><li>mean: 178.19 characters</li><li>max: 593 characters</li></ul> | <ul><li>min: 13 characters</li><li>mean: 1510.36 characters</li><li>max: 29945 characters</li></ul> | <ul><li>0: ~74.40%</li><li>1: ~25.60%</li></ul> |
+* Samples:
+  | query                                                                                                                                                                                                                            | answer                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   | label          |
+  |:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------|
+  | <code>The researchers say that with the right design a Mersey barrage has the potential to become a globally identifiable piece of architectural infrastructure - a 'hydropower landmark' boosting tourism to the region.</code> | <code>Currently there is renewed interest in harnessing the vast tidal resource to combat the twin challenges of climate change and energy security. However, within the UK no tidal barrage proposals have passed the development stage, this is due to a combination of high cost and environmental concerns. This paper demonstrates how a framework, such as the North West Hydro Resource Model can be applied to tidal barrages, with the Mersey barrage as a case study. The model materialised in order to provide developers with a tool to successfully identify the capacity of hydropower schemes in a specific location. A key feature of the resource model is the understanding that there is no single barrier to the utilisation of small hydropower but several obstacles, which together impede development. Thus, this paper contributes in part to a fully holistic treatment of tidal barrages, recognising that apart from energy generation, other environmental, societal and economic opportunities arise and must b...</code> | <code>1</code> |
+  | <code>The researchers say that with the right design a Mersey barrage has the potential to become a globally identifiable piece of architectural infrastructure - a 'hydropower landmark' boosting tourism to the region.</code> | <code>Rainbows contribute to human wellbeing by providing an inspiring connection to nature. Because the rainbow is an atmospheric optical phenomenon that results from the refraction of sunlight by rainwater droplets, changes in precipitation and cloud cover due to anthropogenic climate forcing will alter rainbow distribution. Yet, we lack a basic understanding of the current spatial distribution of rainbows and how climate change might alter this pattern. To assess how climate change might affect rainbow viewing opportunities, we developed a global database of crowd-sourced photographed rainbows, trained an empirical model of rainbow occurrence, and applied this model to present-day climate and three future climate scenarios. Results suggest that the average terrestrial location on Earth currently has 117 ± 71 days per year with conditions suitable for rainbows. By 2100, climate change is likely to generate a 4.0–4.9 % net increase in mean global annual rainbow-days (i.e., days with at leas...</code> | <code>0</code> |
+  | <code>The researchers say that with the right design a Mersey barrage has the potential to become a globally identifiable piece of architectural infrastructure - a 'hydropower landmark' boosting tourism to the region.</code> | <code>The ascendancy of dinosaurs to become dominant components of terrestrial ecosystems was a pivotal event in the history of life, yet the drivers of their early evolution and biodiversity are poorly understood.1Brusatte S.L. Benton M.J. Ruta M. Lloyd G.T. The first 50 Myr of dinosaur evolution: macroevolutionary pattern and morphological disparity.Biol. Lett. 2008; 4: 733-736https://doi.org/10.1098/rsbl.2008.0441Crossref PubMed Scopus (105) Google Scholar,2Irmis R.B. Evaluating hypotheses for the early diversification of dinosaurs.Earth Environ. Sci. Trans. R. Soc. Edinb. 2010; 101: 397-426https://doi.org/10.1017/S1755691011020068Crossref Scopus (94) Google Scholar,3Benton M.J. Forth J. Langer M.C. Models for the rise of the dinosaurs.Curr. Biol. 2014; 24: R87-R95https://doi.org/10.1016/j.cub.2013.11.063Abstract Full Text Full Text PDF PubMed Scopus (93) Google Scholar During their early diversification in the Late Triassic, dinosaurs were initially rare and geographically restricted, on...</code> | <code>0</code> |
+* Loss: [<code>BinaryCrossEntropyLoss</code>](https://sbert.net/docs/package_reference/cross_encoder/losses.html#binarycrossentropyloss) with these parameters:
+  ```json
+  {
+      "activation_fn": "torch.nn.modules.linear.Identity",
+      "pos_weight": 6
+  }
+  ```
+
+### Training Hyperparameters
+#### Non-Default Hyperparameters
+
+- `eval_strategy`: steps
+- `per_device_train_batch_size`: 16
+- `per_device_eval_batch_size`: 16
+- `learning_rate`: 2e-05
+- `warmup_ratio`: 0.1
+- `fp16`: True
+- `dataloader_num_workers`: 4
+- `load_best_model_at_end`: True
+
+#### All Hyperparameters
+<details><summary>Click to expand</summary>
+
+- `overwrite_output_dir`: False
+- `do_predict`: False
+- `eval_strategy`: steps
+- `prediction_loss_only`: True
+- `per_device_train_batch_size`: 16
+- `per_device_eval_batch_size`: 16
+- `per_gpu_train_batch_size`: None
+- `per_gpu_eval_batch_size`: None
+- `gradient_accumulation_steps`: 1
+- `eval_accumulation_steps`: None
+- `torch_empty_cache_steps`: None
+- `learning_rate`: 2e-05
+- `weight_decay`: 0.0
+- `adam_beta1`: 0.9
+- `adam_beta2`: 0.999
+- `adam_epsilon`: 1e-08
+- `max_grad_norm`: 1.0
+- `num_train_epochs`: 3
+- `max_steps`: -1
+- `lr_scheduler_type`: linear
+- `lr_scheduler_kwargs`: {}
+- `warmup_ratio`: 0.1
+- `warmup_steps`: 0
+- `log_level`: passive
+- `log_level_replica`: warning
+- `log_on_each_node`: True
+- `logging_nan_inf_filter`: True
+- `save_safetensors`: True
+- `save_on_each_node`: False
+- `save_only_model`: False
+- `restore_callback_states_from_checkpoint`: False
+- `no_cuda`: False
+- `use_cpu`: False
+- `use_mps_device`: False
+- `seed`: 42
+- `data_seed`: None
+- `jit_mode_eval`: False
+- `use_ipex`: False
+- `bf16`: False
+- `fp16`: True
+- `fp16_opt_level`: O1
+- `half_precision_backend`: auto
+- `bf16_full_eval`: False
+- `fp16_full_eval`: False
+- `tf32`: None
+- `local_rank`: 0
+- `ddp_backend`: None
+- `tpu_num_cores`: None
+- `tpu_metrics_debug`: False
+- `debug`: []
+- `dataloader_drop_last`: False
+- `dataloader_num_workers`: 4
+- `dataloader_prefetch_factor`: None
+- `past_index`: -1
+- `disable_tqdm`: False
+- `remove_unused_columns`: True
+- `label_names`: None
+- `load_best_model_at_end`: True
+- `ignore_data_skip`: False
+- `fsdp`: []
+- `fsdp_min_num_params`: 0
+- `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
+- `tp_size`: 0
+- `fsdp_transformer_layer_cls_to_wrap`: None
+- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
+- `deepspeed`: None
+- `label_smoothing_factor`: 0.0
+- `optim`: adamw_torch
+- `optim_args`: None
+- `adafactor`: False
+- `group_by_length`: False
+- `length_column_name`: length
+- `ddp_find_unused_parameters`: None
+- `ddp_bucket_cap_mb`: None
+- `ddp_broadcast_buffers`: False
+- `dataloader_pin_memory`: True
+- `dataloader_persistent_workers`: False
+- `skip_memory_metrics`: True
+- `use_legacy_prediction_loop`: False
+- `push_to_hub`: False
+- `resume_from_checkpoint`: None
+- `hub_model_id`: None
+- `hub_strategy`: every_save
+- `hub_private_repo`: None
+- `hub_always_push`: False
+- `gradient_checkpointing`: False
+- `gradient_checkpointing_kwargs`: None
+- `include_inputs_for_metrics`: False
+- `include_for_metrics`: []
+- `eval_do_concat_batches`: True
+- `fp16_backend`: auto
+- `push_to_hub_model_id`: None
+- `push_to_hub_organization`: None
+- `mp_parameters`: 
+- `auto_find_batch_size`: False
+- `full_determinism`: False
+- `torchdynamo`: None
+- `ray_scope`: last
+- `ddp_timeout`: 1800
+- `torch_compile`: False
+- `torch_compile_backend`: None
+- `torch_compile_mode`: None
+- `include_tokens_per_second`: False
+- `include_num_input_tokens_seen`: False
+- `neftune_noise_alpha`: None
+- `optim_target_modules`: None
+- `batch_eval_metrics`: False
+- `eval_on_start`: False
+- `use_liger_kernel`: False
+- `eval_use_gather_object`: False
+- `average_tokens_across_devices`: False
+- `prompts`: None
+- `batch_sampler`: batch_sampler
+- `multi_dataset_batch_sampler`: proportional
+
+</details>
+
+### Training Logs
+<details><summary>Click to expand</summary>
+
+| Epoch      | Step      | Training Loss | climate-science-eval_ndcg@10 |
+|:----------:|:---------:|:-------------:|:----------------------------:|
+| 0.0001     | 1         | 6.4826        | -                            |
+| 0.0061     | 100       | 6.3516        | -                            |
+| 0.0121     | 200       | 5.1792        | -                            |
+| 0.0182     | 300       | 2.9628        | -                            |
+| 0.0243     | 400       | 1.8946        | -                            |
+| 0.0304     | 500       | 1.3992        | -                            |
+| 0.0364     | 600       | 1.4469        | -                            |
+| 0.0425     | 700       | 1.1841        | -                            |
+| 0.0486     | 800       | 0.9967        | -                            |
+| 0.0547     | 900       | 0.9914        | -                            |
+| 0.0607     | 1000      | 0.7138        | 0.6113 (+0.3713)             |
+| 0.0668     | 1100      | 0.6944        | -                            |
+| 0.0729     | 1200      | 0.7374        | -                            |
+| 0.0789     | 1300      | 0.7249        | -                            |
+| 0.0850     | 1400      | 0.8826        | -                            |
+| 0.0911     | 1500      | 0.6886        | -                            |
+| 0.0972     | 1600      | 0.8185        | -                            |
+| 0.1032     | 1700      | 0.6946        | -                            |
+| 0.1093     | 1800      | 0.7231        | -                            |
+| 0.1154     | 1900      | 0.668         | -                            |
+| 0.1214     | 2000      | 0.6434        | 0.6325 (+0.3926)             |
+| 0.1275     | 2100      | 0.7417        | -                            |
+| 0.1336     | 2200      | 0.6777        | -                            |
+| 0.1397     | 2300      | 0.779         | -                            |
+| 0.1457     | 2400      | 0.6876        | -                            |
+| 0.1518     | 2500      | 0.6619        | -                            |
+| 0.1579     | 2600      | 0.6626        | -                            |
+| 0.1640     | 2700      | 0.7394        | -                            |
+| 0.1700     | 2800      | 0.6654        | -                            |
+| 0.1761     | 2900      | 0.6026        | -                            |
+| 0.1822     | 3000      | 0.6838        | 0.6417 (+0.4018)             |
+| 0.1882     | 3100      | 0.6423        | -                            |
+| 0.1943     | 3200      | 0.6559        | -                            |
+| 0.2004     | 3300      | 0.6097        | -                            |
+| 0.2065     | 3400      | 0.6564        | -                            |
+| 0.2125     | 3500      | 0.6912        | -                            |
+| 0.2186     | 3600      | 0.6183        | -                            |
+| 0.2247     | 3700      | 0.5585        | -                            |
+| 0.2308     | 3800      | 0.6748        | -                            |
+| 0.2368     | 3900      | 0.6165        | -                            |
+| 0.2429     | 4000      | 0.6358        | 0.6529 (+0.4130)             |
+| 0.2490     | 4100      | 0.6473        | -                            |
+| 0.2550     | 4200      | 0.6766        | -                            |
+| 0.2611     | 4300      | 0.6603        | -                            |
+| 0.2672     | 4400      | 0.5778        | -                            |
+| 0.2733     | 4500      | 0.6732        | -                            |
+| 0.2793     | 4600      | 0.605         | -                            |
+| 0.2854     | 4700      | 0.6943        | -                            |
+| 0.2915     | 4800      | 0.5776        | -                            |
+| 0.2975     | 4900      | 0.706         | -                            |
+| 0.3036     | 5000      | 0.5758        | 0.6559 (+0.4160)             |
+| 0.3097     | 5100      | 0.6596        | -                            |
+| 0.3158     | 5200      | 0.6466        | -                            |
+| 0.3218     | 5300      | 0.6116        | -                            |
+| 0.3279     | 5400      | 0.5654        | -                            |
+| 0.3340     | 5500      | 0.643         | -                            |
+| 0.3401     | 5600      | 0.7281        | -                            |
+| 0.3461     | 5700      | 0.6295        | -                            |
+| 0.3522     | 5800      | 0.6555        | -                            |
+| 0.3583     | 5900      | 0.6671        | -                            |
+| 0.3643     | 6000      | 0.6647        | 0.6537 (+0.4138)             |
+| 0.3704     | 6100      | 0.5458        | -                            |
+| 0.3765     | 6200      | 0.6279        | -                            |
+| 0.3826     | 6300      | 0.6575        | -                            |
+| 0.3886     | 6400      | 0.6206        | -                            |
+| 0.3947     | 6500      | 0.5802        | -                            |
+| 0.4008     | 6600      | 0.7117        | -                            |
+| 0.4068     | 6700      | 0.589         | -                            |
+| 0.4129     | 6800      | 0.6245        | -                            |
+| 0.4190     | 6900      | 0.5346        | -                            |
+| 0.4251     | 7000      | 0.7323        | 0.6559 (+0.4160)             |
+| 0.4311     | 7100      | 0.5407        | -                            |
+| 0.4372     | 7200      | 0.53          | -                            |
+| 0.4433     | 7300      | 0.5586        | -                            |
+| 0.4494     | 7400      | 0.6219        | -                            |
+| 0.4554     | 7500      | 0.6396        | -                            |
+| 0.4615     | 7600      | 0.54          | -                            |
+| 0.4676     | 7700      | 0.6284        | -                            |
+| 0.4736     | 7800      | 0.6021        | -                            |
+| 0.4797     | 7900      | 0.6326        | -                            |
+| 0.4858     | 8000      | 0.6375        | 0.6691 (+0.4291)             |
+| 0.4919     | 8100      | 0.5402        | -                            |
+| 0.4979     | 8200      | 0.582         | -                            |
+| 0.5040     | 8300      | 0.5382        | -                            |
+| 0.5101     | 8400      | 0.581         | -                            |
+| 0.5162     | 8500      | 0.6062        | -                            |
+| 0.5222     | 8600      | 0.5804        | -                            |
+| 0.5283     | 8700      | 0.6233        | -                            |
+| 0.5344     | 8800      | 0.5813        | -                            |
+| 0.5404     | 8900      | 0.5619        | -                            |
+| 0.5465     | 9000      | 0.5328        | 0.6694 (+0.4295)             |
+| 0.5526     | 9100      | 0.5371        | -                            |
+| 0.5587     | 9200      | 0.6534        | -                            |
+| 0.5647     | 9300      | 0.5395        | -                            |
+| 0.5708     | 9400      | 0.577         | -                            |
+| 0.5769     | 9500      | 0.5936        | -                            |
+| 0.5829     | 9600      | 0.5947        | -                            |
+| 0.5890     | 9700      | 0.5806        | -                            |
+| 0.5951     | 9800      | 0.6236        | -                            |
+| 0.6012     | 9900      | 0.6087        | -                            |
+| 0.6072     | 10000     | 0.5466        | 0.6712 (+0.4313)             |
+| 0.6133     | 10100     | 0.6824        | -                            |
+| 0.6194     | 10200     | 0.5657        | -                            |
+| 0.6255     | 10300     | 0.5772        | -                            |
+| 0.6315     | 10400     | 0.6068        | -                            |
+| 0.6376     | 10500     | 0.4815        | -                            |
+| 0.6437     | 10600     | 0.527         | -                            |
+| 0.6497     | 10700     | 0.6041        | -                            |
+| 0.6558     | 10800     | 0.5542        | -                            |
+| 0.6619     | 10900     | 0.5846        | -                            |
+| 0.6680     | 11000     | 0.5559        | 0.6683 (+0.4284)             |
+| 0.6740     | 11100     | 0.6235        | -                            |
+| 0.6801     | 11200     | 0.581         | -                            |
+| 0.6862     | 11300     | 0.5931        | -                            |
+| 0.6923     | 11400     | 0.532         | -                            |
+| 0.6983     | 11500     | 0.5832        | -                            |
+| 0.7044     | 11600     | 0.4815        | -                            |
+| 0.7105     | 11700     | 0.7507        | -                            |
+| 0.7165     | 11800     | 0.555         | -                            |
+| 0.7226     | 11900     | 0.585         | -                            |
+| 0.7287     | 12000     | 0.6486        | 0.6711 (+0.4311)             |
+| 0.7348     | 12100     | 0.6077        | -                            |
+| 0.7408     | 12200     | 0.5116        | -                            |
+| 0.7469     | 12300     | 0.6163        | -                            |
+| 0.7530     | 12400     | 0.6205        | -                            |
+| 0.7590     | 12500     | 0.5086        | -                            |
+| 0.7651     | 12600     | 0.5544        | -                            |
+| 0.7712     | 12700     | 0.4743        | -                            |
+| 0.7773     | 12800     | 0.5854        | -                            |
+| 0.7833     | 12900     | 0.5681        | -                            |
+| 0.7894     | 13000     | 0.6179        | 0.6760 (+0.4360)             |
+| 0.7955     | 13100     | 0.5958        | -                            |
+| 0.8016     | 13200     | 0.5162        | -                            |
+| 0.8076     | 13300     | 0.609         | -                            |
+| 0.8137     | 13400     | 0.4877        | -                            |
+| 0.8198     | 13500     | 0.6157        | -                            |
+| 0.8258     | 13600     | 0.5638        | -                            |
+| 0.8319     | 13700     | 0.5049        | -                            |
+| 0.8380     | 13800     | 0.7226        | -                            |
+| 0.8441     | 13900     | 0.515         | -                            |
+| 0.8501     | 14000     | 0.5564        | 0.6822 (+0.4423)             |
+| 0.8562     | 14100     | 0.5618        | -                            |
+| 0.8623     | 14200     | 0.5448        | -                            |
+| 0.8684     | 14300     | 0.5693        | -                            |
+| 0.8744     | 14400     | 0.6417        | -                            |
+| 0.8805     | 14500     | 0.5609        | -                            |
+| 0.8866     | 14600     | 0.6033        | -                            |
+| 0.8926     | 14700     | 0.6355        | -                            |
+| 0.8987     | 14800     | 0.5322        | -                            |
+| 0.9048     | 14900     | 0.519         | -                            |
+| 0.9109     | 15000     | 0.5662        | 0.6764 (+0.4365)             |
+| 0.9169     | 15100     | 0.593         | -                            |
+| 0.9230     | 15200     | 0.6004        | -                            |
+| 0.9291     | 15300     | 0.5673        | -                            |
+| 0.9351     | 15400     | 0.5142        | -                            |
+| 0.9412     | 15500     | 0.5859        | -                            |
+| 0.9473     | 15600     | 0.6421        | -                            |
+| 0.9534     | 15700     | 0.4822        | -                            |
+| 0.9594     | 15800     | 0.6082        | -                            |
+| 0.9655     | 15900     | 0.5373        | -                            |
+| 0.9716     | 16000     | 0.6102        | 0.6729 (+0.4330)             |
+| 0.9777     | 16100     | 0.5109        | -                            |
+| 0.9837     | 16200     | 0.6156        | -                            |
+| 0.9898     | 16300     | 0.6408        | -                            |
+| 0.9959     | 16400     | 0.5031        | -                            |
+| 1.0019     | 16500     | 0.4652        | -                            |
+| 1.0080     | 16600     | 0.3893        | -                            |
+| 1.0141     | 16700     | 0.6276        | -                            |
+| 1.0202     | 16800     | 0.5526        | -                            |
+| 1.0262     | 16900     | 0.551         | -                            |
+| 1.0323     | 17000     | 0.5066        | 0.6832 (+0.4432)             |
+| 1.0384     | 17100     | 0.5074        | -                            |
+| 1.0444     | 17200     | 0.48          | -                            |
+| 1.0505     | 17300     | 0.6073        | -                            |
+| 1.0566     | 17400     | 0.485         | -                            |
+| 1.0627     | 17500     | 0.4927        | -                            |
+| 1.0687     | 17600     | 0.597         | -                            |
+| 1.0748     | 17700     | 0.4376        | -                            |
+| 1.0809     | 17800     | 0.4935        | -                            |
+| 1.0870     | 17900     | 0.5702        | -                            |
+| 1.0930     | 18000     | 0.4482        | 0.6825 (+0.4426)             |
+| 1.0991     | 18100     | 0.5183        | -                            |
+| 1.1052     | 18200     | 0.4593        | -                            |
+| 1.1112     | 18300     | 0.4775        | -                            |
+| 1.1173     | 18400     | 0.5831        | -                            |
+| 1.1234     | 18500     | 0.4942        | -                            |
+| 1.1295     | 18600     | 0.5684        | -                            |
+| 1.1355     | 18700     | 0.5214        | -                            |
+| 1.1416     | 18800     | 0.5292        | -                            |
+| 1.1477     | 18900     | 0.5163        | -                            |
+| 1.1538     | 19000     | 0.5305        | 0.6868 (+0.4469)             |
+| 1.1598     | 19100     | 0.4507        | -                            |
+| 1.1659     | 19200     | 0.4699        | -                            |
+| 1.1720     | 19300     | 0.4532        | -                            |
+| 1.1780     | 19400     | 0.4853        | -                            |
+| 1.1841     | 19500     | 0.5169        | -                            |
+| 1.1902     | 19600     | 0.5927        | -                            |
+| 1.1963     | 19700     | 0.5777        | -                            |
+| 1.2023     | 19800     | 0.5041        | -                            |
+| 1.2084     | 19900     | 0.5309        | -                            |
+| 1.2145     | 20000     | 0.4426        | 0.6809 (+0.4410)             |
+| 1.2205     | 20100     | 0.54          | -                            |
+| 1.2266     | 20200     | 0.5692        | -                            |
+| 1.2327     | 20300     | 0.5004        | -                            |
+| 1.2388     | 20400     | 0.5044        | -                            |
+| 1.2448     | 20500     | 0.4574        | -                            |
+| 1.2509     | 20600     | 0.6132        | -                            |
+| 1.2570     | 20700     | 0.4477        | -                            |
+| 1.2631     | 20800     | 0.4805        | -                            |
+| 1.2691     | 20900     | 0.6127        | -                            |
+| 1.2752     | 21000     | 0.4349        | 0.6914 (+0.4515)             |
+| 1.2813     | 21100     | 0.6595        | -                            |
+| 1.2873     | 21200     | 0.5234        | -                            |
+| 1.2934     | 21300     | 0.4525        | -                            |
+| 1.2995     | 21400     | 0.3841        | -                            |
+| 1.3056     | 21500     | 0.5215        | -                            |
+| 1.3116     | 21600     | 0.6187        | -                            |
+| 1.3177     | 21700     | 0.4491        | -                            |
+| 1.3238     | 21800     | 0.629         | -                            |
+| 1.3299     | 21900     | 0.6247        | -                            |
+| 1.3359     | 22000     | 0.461         | 0.6858 (+0.4459)             |
+| 1.3420     | 22100     | 0.5351        | -                            |
+| 1.3481     | 22200     | 0.4602        | -                            |
+| 1.3541     | 22300     | 0.4915        | -                            |
+| 1.3602     | 22400     | 0.5056        | -                            |
+| 1.3663     | 22500     | 0.4976        | -                            |
+| 1.3724     | 22600     | 0.4983        | -                            |
+| 1.3784     | 22700     | 0.6245        | -                            |
+| 1.3845     | 22800     | 0.5009        | -                            |
+| 1.3906     | 22900     | 0.4268        | -                            |
+| 1.3966     | 23000     | 0.5552        | 0.6860 (+0.4461)             |
+| 1.4027     | 23100     | 0.5136        | -                            |
+| 1.4088     | 23200     | 0.5308        | -                            |
+| 1.4149     | 23300     | 0.4796        | -                            |
+| 1.4209     | 23400     | 0.5315        | -                            |
+| 1.4270     | 23500     | 0.4997        | -                            |
+| 1.4331     | 23600     | 0.457         | -                            |
+| 1.4392     | 23700     | 0.5553        | -                            |
+| 1.4452     | 23800     | 0.5262        | -                            |
+| 1.4513     | 23900     | 0.3976        | -                            |
+| 1.4574     | 24000     | 0.4542        | 0.6929 (+0.4530)             |
+| 1.4634     | 24100     | 0.5882        | -                            |
+| 1.4695     | 24200     | 0.4332        | -                            |
+| 1.4756     | 24300     | 0.4206        | -                            |
+| 1.4817     | 24400     | 0.5621        | -                            |
+| 1.4877     | 24500     | 0.5347        | -                            |
+| 1.4938     | 24600     | 0.3999        | -                            |
+| 1.4999     | 24700     | 0.4689        | -                            |
+| 1.5060     | 24800     | 0.4581        | -                            |
+| 1.5120     | 24900     | 0.547         | -                            |
+| 1.5181     | 25000     | 0.476         | 0.6919 (+0.4520)             |
+| 1.5242     | 25100     | 0.4884        | -                            |
+| 1.5302     | 25200     | 0.4404        | -                            |
+| 1.5363     | 25300     | 0.4938        | -                            |
+| 1.5424     | 25400     | 0.5362        | -                            |
+| 1.5485     | 25500     | 0.5063        | -                            |
+| 1.5545     | 25600     | 0.5653        | -                            |
+| 1.5606     | 25700     | 0.4717        | -                            |
+| 1.5667     | 25800     | 0.4901        | -                            |
+| 1.5727     | 25900     | 0.5102        | -                            |
+| 1.5788     | 26000     | 0.5277        | 0.6878 (+0.4479)             |
+| 1.5849     | 26100     | 0.496         | -                            |
+| 1.5910     | 26200     | 0.553         | -                            |
+| 1.5970     | 26300     | 0.5712        | -                            |
+| 1.6031     | 26400     | 0.5246        | -                            |
+| 1.6092     | 26500     | 0.5805        | -                            |
+| 1.6153     | 26600     | 0.5651        | -                            |
+| 1.6213     | 26700     | 0.6139        | -                            |
+| 1.6274     | 26800     | 0.4898        | -                            |
+| 1.6335     | 26900     | 0.4464        | -                            |
+| 1.6395     | 27000     | 0.479         | 0.6926 (+0.4527)             |
+| 1.6456     | 27100     | 0.5201        | -                            |
+| 1.6517     | 27200     | 0.3981        | -                            |
+| 1.6578     | 27300     | 0.5541        | -                            |
+| 1.6638     | 27400     | 0.5546        | -                            |
+| 1.6699     | 27500     | 0.4874        | -                            |
+| 1.6760     | 27600     | 0.5388        | -                            |
+| 1.6821     | 27700     | 0.4642        | -                            |
+| 1.6881     | 27800     | 0.5017        | -                            |
+| 1.6942     | 27900     | 0.4948        | -                            |
+| 1.7003     | 28000     | 0.5065        | 0.6970 (+0.4571)             |
+| 1.7063     | 28100     | 0.5501        | -                            |
+| 1.7124     | 28200     | 0.3532        | -                            |
+| 1.7185     | 28300     | 0.5828        | -                            |
+| 1.7246     | 28400     | 0.4659        | -                            |
+| 1.7306     | 28500     | 0.5192        | -                            |
+| 1.7367     | 28600     | 0.4208        | -                            |
+| 1.7428     | 28700     | 0.5869        | -                            |
+| 1.7488     | 28800     | 0.5452        | -                            |
+| 1.7549     | 28900     | 0.5222        | -                            |
+| 1.7610     | 29000     | 0.5656        | 0.6987 (+0.4587)             |
+| 1.7671     | 29100     | 0.5486        | -                            |
+| 1.7731     | 29200     | 0.4706        | -                            |
+| 1.7792     | 29300     | 0.5038        | -                            |
+| 1.7853     | 29400     | 0.4439        | -                            |
+| 1.7914     | 29500     | 0.5442        | -                            |
+| 1.7974     | 29600     | 0.4777        | -                            |
+| 1.8035     | 29700     | 0.5777        | -                            |
+| 1.8096     | 29800     | 0.4981        | -                            |
+| 1.8156     | 29900     | 0.4757        | -                            |
+| 1.8217     | 30000     | 0.498         | 0.6971 (+0.4572)             |
+| 1.8278     | 30100     | 0.5251        | -                            |
+| 1.8339     | 30200     | 0.4121        | -                            |
+| 1.8399     | 30300     | 0.5471        | -                            |
+| 1.8460     | 30400     | 0.4772        | -                            |
+| 1.8521     | 30500     | 0.4986        | -                            |
+| 1.8581     | 30600     | 0.5598        | -                            |
+| 1.8642     | 30700     | 0.4857        | -                            |
+| 1.8703     | 30800     | 0.3509        | -                            |
+| 1.8764     | 30900     | 0.5719        | -                            |
+| 1.8824     | 31000     | 0.5183        | 0.7000 (+0.4600)             |
+| 1.8885     | 31100     | 0.3952        | -                            |
+| 1.8946     | 31200     | 0.5221        | -                            |
+| 1.9007     | 31300     | 0.4777        | -                            |
+| 1.9067     | 31400     | 0.4371        | -                            |
+| 1.9128     | 31500     | 0.5726        | -                            |
+| 1.9189     | 31600     | 0.5451        | -                            |
+| 1.9249     | 31700     | 0.5352        | -                            |
+| 1.9310     | 31800     | 0.4411        | -                            |
+| 1.9371     | 31900     | 0.4589        | -                            |
+| 1.9432     | 32000     | 0.4623        | 0.6922 (+0.4523)             |
+| 1.9492     | 32100     | 0.4656        | -                            |
+| 1.9553     | 32200     | 0.4595        | -                            |
+| 1.9614     | 32300     | 0.5686        | -                            |
+| 1.9675     | 32400     | 0.3952        | -                            |
+| 1.9735     | 32500     | 0.3992        | -                            |
+| 1.9796     | 32600     | 0.4397        | -                            |
+| 1.9857     | 32700     | 0.5823        | -                            |
+| 1.9917     | 32800     | 0.3741        | -                            |
+| 1.9978     | 32900     | 0.5914        | -                            |
+| 2.0039     | 33000     | 0.3066        | 0.7022 (+0.4623)             |
+| 2.0100     | 33100     | 0.3759        | -                            |
+| 2.0160     | 33200     | 0.4164        | -                            |
+| 2.0221     | 33300     | 0.3911        | -                            |
+| 2.0282     | 33400     | 0.4269        | -                            |
+| 2.0342     | 33500     | 0.397         | -                            |
+| 2.0403     | 33600     | 0.378         | -                            |
+| 2.0464     | 33700     | 0.5975        | -                            |
+| 2.0525     | 33800     | 0.4485        | -                            |
+| 2.0585     | 33900     | 0.3636        | -                            |
+| 2.0646     | 34000     | 0.3081        | 0.7009 (+0.4610)             |
+| 2.0707     | 34100     | 0.4204        | -                            |
+| 2.0768     | 34200     | 0.4379        | -                            |
+| 2.0828     | 34300     | 0.4619        | -                            |
+| 2.0889     | 34400     | 0.3795        | -                            |
+| 2.0950     | 34500     | 0.4356        | -                            |
+| 2.1010     | 34600     | 0.4095        | -                            |
+| 2.1071     | 34700     | 0.454         | -                            |
+| 2.1132     | 34800     | 0.4248        | -                            |
+| 2.1193     | 34900     | 0.3987        | -                            |
+| 2.1253     | 35000     | 0.4074        | 0.6997 (+0.4598)             |
+| 2.1314     | 35100     | 0.4302        | -                            |
+| 2.1375     | 35200     | 0.4459        | -                            |
+| 2.1436     | 35300     | 0.4961        | -                            |
+| 2.1496     | 35400     | 0.4565        | -                            |
+| 2.1557     | 35500     | 0.438         | -                            |
+| 2.1618     | 35600     | 0.4256        | -                            |
+| 2.1678     | 35700     | 0.4943        | -                            |
+| 2.1739     | 35800     | 0.4378        | -                            |
+| 2.1800     | 35900     | 0.4059        | -                            |
+| 2.1861     | 36000     | 0.4706        | 0.7022 (+0.4623)             |
+| 2.1921     | 36100     | 0.4848        | -                            |
+| 2.1982     | 36200     | 0.5028        | -                            |
+| 2.2043     | 36300     | 0.4847        | -                            |
+| 2.2103     | 36400     | 0.3933        | -                            |
+| 2.2164     | 36500     | 0.4298        | -                            |
+| 2.2225     | 36600     | 0.5339        | -                            |
+| 2.2286     | 36700     | 0.3225        | -                            |
+| 2.2346     | 36800     | 0.3906        | -                            |
+| 2.2407     | 36900     | 0.3294        | -                            |
+| 2.2468     | 37000     | 0.4511        | 0.6971 (+0.4572)             |
+| 2.2529     | 37100     | 0.3817        | -                            |
+| 2.2589     | 37200     | 0.4822        | -                            |
+| 2.2650     | 37300     | 0.3975        | -                            |
+| 2.2711     | 37400     | 0.4482        | -                            |
+| 2.2771     | 37500     | 0.3826        | -                            |
+| 2.2832     | 37600     | 0.5013        | -                            |
+| 2.2893     | 37700     | 0.3956        | -                            |
+| 2.2954     | 37800     | 0.438         | -                            |
+| 2.3014     | 37900     | 0.5253        | -                            |
+| 2.3075     | 38000     | 0.3576        | 0.7000 (+0.4601)             |
+| 2.3136     | 38100     | 0.4061        | -                            |
+| 2.3197     | 38200     | 0.456         | -                            |
+| 2.3257     | 38300     | 0.5257        | -                            |
+| 2.3318     | 38400     | 0.5533        | -                            |
+| 2.3379     | 38500     | 0.4898        | -                            |
+| 2.3439     | 38600     | 0.3854        | -                            |
+| 2.3500     | 38700     | 0.4025        | -                            |
+| 2.3561     | 38800     | 0.5514        | -                            |
+| 2.3622     | 38900     | 0.441         | -                            |
+| 2.3682     | 39000     | 0.4563        | 0.7003 (+0.4603)             |
+| 2.3743     | 39100     | 0.436         | -                            |
+| 2.3804     | 39200     | 0.4162        | -                            |
+| 2.3864     | 39300     | 0.5437        | -                            |
+| 2.3925     | 39400     | 0.4212        | -                            |
+| 2.3986     | 39500     | 0.3891        | -                            |
+| 2.4047     | 39600     | 0.3907        | -                            |
+| 2.4107     | 39700     | 0.4422        | -                            |
+| 2.4168     | 39800     | 0.4499        | -                            |
+| 2.4229     | 39900     | 0.4889        | -                            |
+| 2.4290     | 40000     | 0.4213        | 0.7018 (+0.4619)             |
+| 2.4350     | 40100     | 0.4689        | -                            |
+| 2.4411     | 40200     | 0.4344        | -                            |
+| 2.4472     | 40300     | 0.4739        | -                            |
+| 2.4532     | 40400     | 0.4998        | -                            |
+| 2.4593     | 40500     | 0.4831        | -                            |
+| 2.4654     | 40600     | 0.4539        | -                            |
+| 2.4715     | 40700     | 0.4089        | -                            |
+| 2.4775     | 40800     | 0.3621        | -                            |
+| 2.4836     | 40900     | 0.4391        | -                            |
+| 2.4897     | 41000     | 0.4505        | 0.7044 (+0.4645)             |
+| 2.4957     | 41100     | 0.5392        | -                            |
+| 2.5018     | 41200     | 0.3973        | -                            |
+| 2.5079     | 41300     | 0.4245        | -                            |
+| 2.5140     | 41400     | 0.3979        | -                            |
+| 2.5200     | 41500     | 0.4979        | -                            |
+| 2.5261     | 41600     | 0.4346        | -                            |
+| 2.5322     | 41700     | 0.5294        | -                            |
+| 2.5383     | 41800     | 0.2816        | -                            |
+| 2.5443     | 41900     | 0.4917        | -                            |
+| **2.5504** | **42000** | **0.5214**    | **0.7068 (+0.4669)**         |
+| 2.5565     | 42100     | 0.4735        | -                            |
+| 2.5625     | 42200     | 0.3989        | -                            |
+| 2.5686     | 42300     | 0.397         | -                            |
+| 2.5747     | 42400     | 0.4202        | -                            |
+| 2.5808     | 42500     | 0.3813        | -                            |
+| 2.5868     | 42600     | 0.3742        | -                            |
+| 2.5929     | 42700     | 0.3593        | -                            |
+| 2.5990     | 42800     | 0.4132        | -                            |
+| 2.6051     | 42900     | 0.4089        | -                            |
+| 2.6111     | 43000     | 0.555         | 0.7057 (+0.4658)             |
+| 2.6172     | 43100     | 0.3949        | -                            |
+| 2.6233     | 43200     | 0.3216        | -                            |
+| 2.6293     | 43300     | 0.4265        | -                            |
+| 2.6354     | 43400     | 0.4529        | -                            |
+| 2.6415     | 43500     | 0.5047        | -                            |
+| 2.6476     | 43600     | 0.5522        | -                            |
+| 2.6536     | 43700     | 0.4635        | -                            |
+| 2.6597     | 43800     | 0.3012        | -                            |
+| 2.6658     | 43900     | 0.3738        | -                            |
+| 2.6718     | 44000     | 0.4507        | 0.7040 (+0.4641)             |
+| 2.6779     | 44100     | 0.4097        | -                            |
+| 2.6840     | 44200     | 0.3425        | -                            |
+| 2.6901     | 44300     | 0.3934        | -                            |
+| 2.6961     | 44400     | 0.507         | -                            |
+| 2.7022     | 44500     | 0.4207        | -                            |
+| 2.7083     | 44600     | 0.3949        | -                            |
+| 2.7144     | 44700     | 0.4073        | -                            |
+| 2.7204     | 44800     | 0.547         | -                            |
+| 2.7265     | 44900     | 0.5141        | -                            |
+| 2.7326     | 45000     | 0.3943        | 0.7045 (+0.4646)             |
+| 2.7386     | 45100     | 0.4786        | -                            |
+| 2.7447     | 45200     | 0.4747        | -                            |
+| 2.7508     | 45300     | 0.4123        | -                            |
+| 2.7569     | 45400     | 0.5173        | -                            |
+| 2.7629     | 45500     | 0.3601        | -                            |
+| 2.7690     | 45600     | 0.4944        | -                            |
+| 2.7751     | 45700     | 0.3822        | -                            |
+| 2.7812     | 45800     | 0.5818        | -                            |
+| 2.7872     | 45900     | 0.3503        | -                            |
+| 2.7933     | 46000     | 0.4496        | 0.7039 (+0.4640)             |
+| 2.7994     | 46100     | 0.4341        | -                            |
+| 2.8054     | 46200     | 0.5068        | -                            |
+| 2.8115     | 46300     | 0.4157        | -                            |
+| 2.8176     | 46400     | 0.5226        | -                            |
+| 2.8237     | 46500     | 0.4521        | -                            |
+| 2.8297     | 46600     | 0.3809        | -                            |
+| 2.8358     | 46700     | 0.4364        | -                            |
+| 2.8419     | 46800     | 0.3719        | -                            |
+| 2.8479     | 46900     | 0.4458        | -                            |
+| 2.8540     | 47000     | 0.3888        | 0.7036 (+0.4636)             |
+| 2.8601     | 47100     | 0.3331        | -                            |
+| 2.8662     | 47200     | 0.4155        | -                            |
+| 2.8722     | 47300     | 0.4436        | -                            |
+| 2.8783     | 47400     | 0.4629        | -                            |
+| 2.8844     | 47500     | 0.4362        | -                            |
+| 2.8905     | 47600     | 0.551         | -                            |
+| 2.8965     | 47700     | 0.4062        | -                            |
+| 2.9026     | 47800     | 0.4636        | -                            |
+| 2.9087     | 47900     | 0.2969        | -                            |
+| 2.9147     | 48000     | 0.4171        | 0.7035 (+0.4636)             |
+| 2.9208     | 48100     | 0.499         | -                            |
+| 2.9269     | 48200     | 0.4536        | -                            |
+| 2.9330     | 48300     | 0.4865        | -                            |
+| 2.9390     | 48400     | 0.4162        | -                            |
+| 2.9451     | 48500     | 0.4401        | -                            |
+| 2.9512     | 48600     | 0.4846        | -                            |
+| 2.9573     | 48700     | 0.3991        | -                            |
+| 2.9633     | 48800     | 0.3574        | -                            |
+| 2.9694     | 48900     | 0.4327        | -                            |
+| 2.9755     | 49000     | 0.3185        | 0.7040 (+0.4641)             |
+| 2.9815     | 49100     | 0.4635        | -                            |
+| 2.9876     | 49200     | 0.4235        | -                            |
+| 2.9937     | 49300     | 0.4913        | -                            |
+| 2.9998     | 49400     | 0.4842        | -                            |
+| -1         | -1        | -             | 0.7068 (+0.4669)             |
+
+* The bold row denotes the saved checkpoint.
+</details>
+
+### Framework Versions
+- Python: 3.11.12
+- Sentence Transformers: 4.1.0
+- Transformers: 4.51.3
+- PyTorch: 2.6.0+cu124
+- Accelerate: 1.6.0
+- Datasets: 3.6.0
+- Tokenizers: 0.21.1
+
+## Citation
+
+### BibTeX
+
+#### Sentence Transformers
+```bibtex
+@inproceedings{reimers-2019-sentence-bert,
+    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
+    author = "Reimers, Nils and Gurevych, Iryna",
+    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
+    month = "11",
+    year = "2019",
+    publisher = "Association for Computational Linguistics",
+    url = "https://arxiv.org/abs/1908.10084",
+}
+```
+
+<!--
+## Glossary
+
+*Clearly define terms in order to be accessible across audiences.*
+-->
+
+<!--
+## Model Card Authors
+
+*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
+-->
+
+<!--
+## Model Card Contact
+
+*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
+-->

config.json

@@ -0,0 +1,35 @@
+{
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 384,
+  "id2label": {
+    "0": "LABEL_0"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 1536,
+  "label2id": {
+    "LABEL_0": 0
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 6,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "sentence_transformers": {
+    "activation_fn": "torch.nn.modules.linear.Identity",
+    "version": "4.1.0"
+  },
+  "torch_dtype": "float32",
+  "transformers_version": "4.51.3",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

eval/CrossEncoderRerankingEvaluator_climate-science-eval_results_@10.csv

@@ -0,0 +1,50 @@
+epoch,steps,MAP,MRR@10,NDCG@10
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+0.7894097643915472,13000,0.6352514278490089,0.6260393724493526,0.6759545915276507
+0.8501335924216663,14000,0.6414245179362174,0.6324975140537875,0.68221754821104
+0.9108574204517853,15000,0.63580537961511,0.6265778279240853,0.6764458796640935
+0.9715812484819043,16000,0.6334307576571357,0.6239455504174585,0.6729475472136887
+1.0323050765120234,17000,0.6433090568567137,0.6343057490652179,0.6831532023359758
+1.0930289045421424,18000,0.6420118886585633,0.6331267172498549,0.6824744915611504
+1.1537527325722614,19000,0.6441327076149225,0.6355933362395397,0.6868371199224136
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final/README.md

@@ -0,0 +1,866 @@
+---
+language:
+- en
+license: apache-2.0
+tags:
+- sentence-transformers
+- cross-encoder
+- generated_from_trainer
+- dataset_size:263476
+- loss:BinaryCrossEntropyLoss
+base_model: cross-encoder/ms-marco-MiniLM-L6-v2
+pipeline_tag: text-ranking
+library_name: sentence-transformers
+metrics:
+- map
+- mrr@10
+- ndcg@10
+model-index:
+- name: Climate-Science-Reranker
+  results:
+  - task:
+      type: cross-encoder-reranking
+      name: Cross Encoder Reranking
+    dataset:
+      name: climate science eval
+      type: climate-science-eval
+    metrics:
+    - type: map
+      value: 0.6629
+      name: Map
+    - type: mrr@10
+      value: 0.6554
+      name: Mrr@10
+    - type: ndcg@10
+      value: 0.7068
+      name: Ndcg@10
+---
+
+# Climate-Science-Reranker
+
+This is a [Cross Encoder](https://www.sbert.net/docs/cross_encoder/usage/usage.html) model finetuned from [cross-encoder/ms-marco-MiniLM-L6-v2](https://huggingface.co/cross-encoder/ms-marco-MiniLM-L6-v2) using the [sentence-transformers](https://www.SBERT.net) library. It computes scores for pairs of texts, which can be used for text reranking and semantic search.
+
+## Model Details
+
+### Model Description
+- **Model Type:** Cross Encoder
+- **Base model:** [cross-encoder/ms-marco-MiniLM-L6-v2](https://huggingface.co/cross-encoder/ms-marco-MiniLM-L6-v2) <!-- at revision ce0834f22110de6d9222af7a7a03628121708969 -->
+- **Maximum Sequence Length:** 512 tokens
+- **Number of Output Labels:** 1 label
+<!-- - **Training Dataset:** Unknown -->
+- **Language:** en
+- **License:** apache-2.0
+
+### Model Sources
+
+- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
+- **Documentation:** [Cross Encoder Documentation](https://www.sbert.net/docs/cross_encoder/usage/usage.html)
+- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
+- **Hugging Face:** [Cross Encoders on Hugging Face](https://huggingface.co/models?library=sentence-transformers&other=cross-encoder)
+
+## Usage
+
+### Direct Usage (Sentence Transformers)
+
+First install the Sentence Transformers library:
+
+```bash
+pip install -U sentence-transformers
+```
+
+Then you can load this model and run inference.
+```python
+from sentence_transformers import CrossEncoder
+
+# Download from the 🤗 Hub
+model = CrossEncoder("cross_encoder_model_id")
+# Get scores for pairs of texts
+pairs = [
+    ["The researchers say that with the right design a Mersey barrage has the potential to become a globally identifiable piece of architectural infrastructure - a 'hydropower landmark' boosting tourism to the region.", 'Currently there is renewed interest in harnessing the vast tidal resource to combat the twin challenges of climate change and energy security. However, within the UK no tidal barrage proposals have passed the development stage, this is due to a combination of high cost and environmental concerns. This paper demonstrates how a framework, such as the North West Hydro Resource Model can be applied to tidal barrages, with the Mersey barrage as a case study. The model materialised in order to provide developers with a tool to successfully identify the capacity of hydropower schemes in a specific location. A key feature of the resource model is the understanding that there is no single barrier to the utilisation of small hydropower but several obstacles, which together impede development. Thus, this paper contributes in part to a fully holistic treatment of tidal barrages, recognising that apart from energy generation, other environmental, societal and economic opportunities arise and must be fully investigated for robust decision-making. This study demonstrates how considering the societal needs of the people and the necessity for compensatory habitats, for example, an organic architectural design has developed, which aims to enhance rather than detract from the Mersey.'],
+    ["The researchers say that with the right design a Mersey barrage has the potential to become a globally identifiable piece of architectural infrastructure - a 'hydropower landmark' boosting tourism to the region.", 'Rainbows contribute to human wellbeing by providing an inspiring connection to nature. Because the rainbow is an atmospheric optical phenomenon that results from the refraction of sunlight by rainwater droplets, changes in precipitation and cloud cover due to anthropogenic climate forcing will alter rainbow distribution. Yet, we lack a basic understanding of the current spatial distribution of rainbows and how climate change might alter this pattern. To assess how climate change might affect rainbow viewing opportunities, we developed a global database of crowd-sourced photographed rainbows, trained an empirical model of rainbow occurrence, and applied this model to present-day climate and three future climate scenarios. Results suggest that the average terrestrial location on Earth currently has 117 ± 71 days per year with conditions suitable for rainbows. By 2100, climate change is likely to generate a 4.0–4.9 % net increase in mean global annual rainbow-days (i.e., days with at least one rainbow), with the greatest change under the highest emission scenario. Around 21–34 % of land areas will lose rainbow-days and 66–79 % will gain rainbow-days, with rainbow gain hotspots mainly in high-latitude and high-elevation regions with smaller human populations. Our research demonstrates that alterations to non-tangible environmental attributes due to climate change could be significant and are worthy of consideration and mitigation.'],
+    ["The researchers say that with the right design a Mersey barrage has the potential to become a globally identifiable piece of architectural infrastructure - a 'hydropower landmark' boosting tourism to the region.", 'The ascendancy of dinosaurs to become dominant components of terrestrial ecosystems was a pivotal event in the history of life, yet the drivers of their early evolution and biodiversity are poorly understood.1Brusatte S.L. Benton M.J. Ruta M. Lloyd G.T. The first 50 Myr of dinosaur evolution: macroevolutionary pattern and morphological disparity.Biol. Lett. 2008; 4: 733-736https://doi.org/10.1098/rsbl.2008.0441Crossref PubMed Scopus (105) Google Scholar,2Irmis R.B. Evaluating hypotheses for the early diversification of dinosaurs.Earth Environ. Sci. Trans. R. Soc. Edinb. 2010; 101: 397-426https://doi.org/10.1017/S1755691011020068Crossref Scopus (94) Google Scholar,3Benton M.J. Forth J. Langer M.C. Models for the rise of the dinosaurs.Curr. Biol. 2014; 24: R87-R95https://doi.org/10.1016/j.cub.2013.11.063Abstract Full Text Full Text PDF PubMed Scopus (93) Google Scholar During their early diversification in the Late Triassic, dinosaurs were initially rare and geographically restricted, only attaining wider distributions and greater abundance following the end-Triassic mass extinction event.4Brusatte S.L. Benton M.J. Ruta M. Lloyd G.T. Superiority, competition, and opportunism in the evolutionary radiation of dinosaurs.Science. 2008; 321: 1485-1488https://doi.org/10.1126/science.1161833Crossref PubMed Scopus (334) Google Scholar,5Langer M.C. Ezcurra M.D. Bittencourt J.S. Novas F.E. The origin and early evolution of dinosaurs.Biol. Rev. Camb. Philos. Soc. 2010; 85: 55-110https://doi.org/10.1111/j.1469-185X.2009.00094.xCrossref PubMed Scopus (212) Google Scholar,6Langer M.C. Godoy P.L. So volcanoes created the dinosaurs? a quantitative characterization of the early evolution of terrestrial pan-aves.Front. Earth Sci. 2022; 10https://doi.org/10.3389/feart.2022.899562Crossref PubMed Scopus (3) Google Scholar This pattern is consistent with an opportunistic expansion model, initiated by the extinction of co-occurring groups such as aetosaurs, rauisuchians, and therapsids.4Brusatte S.L. Benton M.J. Ruta M. Lloyd G.T. Superiority, competition, and opportunism in the evolutionary radiation of dinosaurs.Science. 2008; 321: 1485-1488https://doi.org/10.1126/science.1161833Crossref PubMed Scopus (334) Google Scholar,7Tucker M.E. Benton M.J. Triassic environments, climates and reptile evolution.Palaeogeogr. Palaeoclimatol. Palaeoecol. 1982; 40: 361-379https://doi.org/10.1016/0031-0182(82)90034-7Crossref Scopus (89) Google Scholar,8Benton M.J. Dinosaur success in the triassic: a noncompetitive ecological model.Q. Rev. Biol. 1983; 58: 29-55Crossref Scopus (170) Google Scholar However, this pattern could instead be a response to changes in global climatic distributions through the Triassic to Jurassic transition, especially given the increasing evidence that climate played a key role in constraining Triassic dinosaur distributions.7Tucker M.E. Benton M.J. Triassic environments, climates and reptile evolution.Palaeogeogr. Palaeoclimatol. Palaeoecol. 1982; 40: 361-379https://doi.org/10.1016/0031-0182(82)90034-7Crossref Scopus (89) Google Scholar,9Whiteside J.H. Lindström S. Irmis R.B. Glasspool I.J. Schaller M.F. Dunlavey M. Nesbitt S.J. Smith N.D. Turner A.H. Extreme ecosystem instability suppressed tropical dinosaur dominance for 30 million years.Proc. Natl. Acad. Sci. USA. 2015; 112: 7909-7913https://doi.org/10.1073/pnas.1505252112Crossref PubMed Scopus (61) Google Scholar,10Bernardi M. Gianolla P. Petti F.M. Mietto P. Benton M.J. Dinosaur diversification linked with the Carnian pluvial episode.Nat. Commun. 2018; 9: 1499https://doi.org/10.1038/s41467-018-03996-1Crossref PubMed Scopus (87) Google Scholar,11Lovelace D.M. Hartman S.A. Mathewson P.D. Linzmeier B.J. Porter W.P. Modeling Dragons: using linked mechanistic physiological and microclimate models to explore environmental, physiological, and morphological constraints on the early evolution of dinosaurs.PLoS One. 2020; 15e0223872https://doi.org/10.1371/journal.pone.0223872Crossref Scopus (8) Google Scholar,12Mancuso A.C. Benavente C.A. Irmis R.B. Mundil R. Evidence for the Carnian pluvial episode in Gondwana: new multiproxy climate records and their bearing on early dinosaur diversification.Gondwana Res. 2020; 86: 104-125https://doi.org/10.1016/j.gr.2020.05.009Crossref Scopus (35) Google Scholar,13Mancuso A.C. Irmis R.B. Pedernera T.E. Gaetano L.C. Benavente C.A. Breeden III B.T. Paleoenvironmental and biotic changes in the late triassic of Argentina: testing hypotheses of abiotic forcing at the basin scale.Front. Earth Sci. 2022; 10https://doi.org/10.3389/feart.2022.883788Crossref PubMed Scopus (4) Google Scholar,14Kent D.V. Clemmensen L.B. Northward dispersal of dinosaurs from Gondwana to Greenland at the mid-Norian (215–212 Ma, Late Triassic) dip in atmospheric pCO2.Proc. Natl. Acad. Sci. USA. 2021; 118e2020778118https://doi.org/10.1073/pnas.2020778118Crossref Scopus (16) Google Scholar,15Griffin C.T. Wynd B.M. Munyikwa D. Broderick T.J. Zondo M. Tolan S. Langer M.C. Nesbitt S.J. Taruvinga H.R. Africa\'s oldest dinosaurs reveal early suppression of dinosaur distribution.Nature. 2022; 609: 313-319https://doi.org/10.1038/s41586-022-05133-xCrossref PubMed Scopus (4) Google Scholar,16Olsen P. Sha J. Fang Y. Chang C. Whiteside J.H. Kinney S. Sues H.-D. Kent D. Schaller M. Vajda V. Arctic ice and the ecological rise of the dinosaurs.Sci. Adv. 2022; 8eabo6342https://doi.org/10.1126/sciadv.abo6342Crossref Scopus (5) Google Scholar Here, we test this hypothesis and elucidate how climate influenced early dinosaur distribution by quantitatively examining changes in dinosaur and tetrapod "climatic niche space" across the Triassic-Jurassic boundary. Statistical analyses show that Late Triassic sauropodomorph dinosaurs occupied a more restricted climatic niche space than other tetrapods and dinosaurs, being excluded from the hottest, low-latitude climate zones. A subsequent, earliest Jurassic expansion of sauropodomorph geographic distribution is linked to the expansion of their preferred climatic conditions. Evolutionary model-fitting analyses provide evidence for an important evolutionary shift from cooler to warmer climatic niches during the origin of Sauropoda. These results are consistent with the hypothesis that global abundance of sauropodomorph dinosaurs was facilitated by climatic change and provide support for the key role of climate in the ascendancy of dinosaurs.'],
+    ["The researchers say that with the right design a Mersey barrage has the potential to become a globally identifiable piece of architectural infrastructure - a 'hydropower landmark' boosting tourism to the region.", 'The development of technologies to slow climate change has been identified as a global imperative. Nonetheless, such ‘green’ technologies can potentially have negative impacts on biodiversity. We explored how climate change and the mining of lithium for green technologies influence surface water availability, primary productivity and the abundance of three threatened and economically important flamingo species in the ‘Lithium Triangle’ of the Chilean Andes. We combined climate and primary productivity data with remotely sensed measures of surface water levels and a 30-year dataset on flamingo abundance using structural equation modelling. We found that, regionally, flamingo abundance fluctuated dramatically from year-to-year in response to variation in surface water levels and primary productivity but did not exhibit any temporal trends. Locally, in the Salar de Atacama—where lithium mining is focused—we found that mining was negatively correlated with the abundance of two of the three flamingo species. These results suggest continued increases in lithium mining and declines in surface water could soon have dramatic effects on flamingo abundance across their range. Efforts to slow the expansion of mining and the impacts of climate change are, therefore, urgently needed to benefit local biodiversity and the local human economy that depends on it.'],
+    ["The researchers say that with the right design a Mersey barrage has the potential to become a globally identifiable piece of architectural infrastructure - a 'hydropower landmark' boosting tourism to the region.", 'Rivers can abruptly shift pathways in rare events called avulsions, which cause devastating floods. The controls on avulsion locations are poorly understood as a result of sparse data on such features. We analyzed nearly 50 years of satellite imagery and documented 113 avulsions across the globe that indicate three distinct controls on avulsion location. Avulsions on fans coincide with valley-confinement change, whereas avulsions on deltas are primarily clustered within the backwater zone, indicating a control by spatial flow deceleration or acceleration during floods. However, 38% of avulsions on deltas occurred upstream of backwater effects. These events occurred in steep, sediment-rich rivers in tropical and desert environments. Our results indicate that avulsion location on deltas is set by the upstream extent of flood-driven erosion, which is typically limited to the backwater zone but can extend far upstream in steep, sediment-laden rivers. Our findings elucidate how avulsion hazards might respond to land use and climate change.'],
+]
+scores = model.predict(pairs)
+print(scores.shape)
+# (5,)
+
+# Or rank different texts based on similarity to a single text
+ranks = model.rank(
+    "The researchers say that with the right design a Mersey barrage has the potential to become a globally identifiable piece of architectural infrastructure - a 'hydropower landmark' boosting tourism to the region.",
+    [
+        'Currently there is renewed interest in harnessing the vast tidal resource to combat the twin challenges of climate change and energy security. However, within the UK no tidal barrage proposals have passed the development stage, this is due to a combination of high cost and environmental concerns. This paper demonstrates how a framework, such as the North West Hydro Resource Model can be applied to tidal barrages, with the Mersey barrage as a case study. The model materialised in order to provide developers with a tool to successfully identify the capacity of hydropower schemes in a specific location. A key feature of the resource model is the understanding that there is no single barrier to the utilisation of small hydropower but several obstacles, which together impede development. Thus, this paper contributes in part to a fully holistic treatment of tidal barrages, recognising that apart from energy generation, other environmental, societal and economic opportunities arise and must be fully investigated for robust decision-making. This study demonstrates how considering the societal needs of the people and the necessity for compensatory habitats, for example, an organic architectural design has developed, which aims to enhance rather than detract from the Mersey.',
+        'Rainbows contribute to human wellbeing by providing an inspiring connection to nature. Because the rainbow is an atmospheric optical phenomenon that results from the refraction of sunlight by rainwater droplets, changes in precipitation and cloud cover due to anthropogenic climate forcing will alter rainbow distribution. Yet, we lack a basic understanding of the current spatial distribution of rainbows and how climate change might alter this pattern. To assess how climate change might affect rainbow viewing opportunities, we developed a global database of crowd-sourced photographed rainbows, trained an empirical model of rainbow occurrence, and applied this model to present-day climate and three future climate scenarios. Results suggest that the average terrestrial location on Earth currently has 117 ± 71 days per year with conditions suitable for rainbows. By 2100, climate change is likely to generate a 4.0–4.9 % net increase in mean global annual rainbow-days (i.e., days with at least one rainbow), with the greatest change under the highest emission scenario. Around 21–34 % of land areas will lose rainbow-days and 66–79 % will gain rainbow-days, with rainbow gain hotspots mainly in high-latitude and high-elevation regions with smaller human populations. Our research demonstrates that alterations to non-tangible environmental attributes due to climate change could be significant and are worthy of consideration and mitigation.',
+        'The ascendancy of dinosaurs to become dominant components of terrestrial ecosystems was a pivotal event in the history of life, yet the drivers of their early evolution and biodiversity are poorly understood.1Brusatte S.L. Benton M.J. Ruta M. Lloyd G.T. The first 50 Myr of dinosaur evolution: macroevolutionary pattern and morphological disparity.Biol. Lett. 2008; 4: 733-736https://doi.org/10.1098/rsbl.2008.0441Crossref PubMed Scopus (105) Google Scholar,2Irmis R.B. Evaluating hypotheses for the early diversification of dinosaurs.Earth Environ. Sci. Trans. R. Soc. Edinb. 2010; 101: 397-426https://doi.org/10.1017/S1755691011020068Crossref Scopus (94) Google Scholar,3Benton M.J. Forth J. Langer M.C. Models for the rise of the dinosaurs.Curr. Biol. 2014; 24: R87-R95https://doi.org/10.1016/j.cub.2013.11.063Abstract Full Text Full Text PDF PubMed Scopus (93) Google Scholar During their early diversification in the Late Triassic, dinosaurs were initially rare and geographically restricted, only attaining wider distributions and greater abundance following the end-Triassic mass extinction event.4Brusatte S.L. Benton M.J. Ruta M. Lloyd G.T. Superiority, competition, and opportunism in the evolutionary radiation of dinosaurs.Science. 2008; 321: 1485-1488https://doi.org/10.1126/science.1161833Crossref PubMed Scopus (334) Google Scholar,5Langer M.C. Ezcurra M.D. Bittencourt J.S. Novas F.E. The origin and early evolution of dinosaurs.Biol. Rev. Camb. Philos. Soc. 2010; 85: 55-110https://doi.org/10.1111/j.1469-185X.2009.00094.xCrossref PubMed Scopus (212) Google Scholar,6Langer M.C. Godoy P.L. So volcanoes created the dinosaurs? a quantitative characterization of the early evolution of terrestrial pan-aves.Front. Earth Sci. 2022; 10https://doi.org/10.3389/feart.2022.899562Crossref PubMed Scopus (3) Google Scholar This pattern is consistent with an opportunistic expansion model, initiated by the extinction of co-occurring groups such as aetosaurs, rauisuchians, and therapsids.4Brusatte S.L. Benton M.J. Ruta M. Lloyd G.T. Superiority, competition, and opportunism in the evolutionary radiation of dinosaurs.Science. 2008; 321: 1485-1488https://doi.org/10.1126/science.1161833Crossref PubMed Scopus (334) Google Scholar,7Tucker M.E. Benton M.J. Triassic environments, climates and reptile evolution.Palaeogeogr. Palaeoclimatol. Palaeoecol. 1982; 40: 361-379https://doi.org/10.1016/0031-0182(82)90034-7Crossref Scopus (89) Google Scholar,8Benton M.J. Dinosaur success in the triassic: a noncompetitive ecological model.Q. Rev. Biol. 1983; 58: 29-55Crossref Scopus (170) Google Scholar However, this pattern could instead be a response to changes in global climatic distributions through the Triassic to Jurassic transition, especially given the increasing evidence that climate played a key role in constraining Triassic dinosaur distributions.7Tucker M.E. Benton M.J. Triassic environments, climates and reptile evolution.Palaeogeogr. Palaeoclimatol. Palaeoecol. 1982; 40: 361-379https://doi.org/10.1016/0031-0182(82)90034-7Crossref Scopus (89) Google Scholar,9Whiteside J.H. Lindström S. Irmis R.B. Glasspool I.J. Schaller M.F. Dunlavey M. Nesbitt S.J. Smith N.D. Turner A.H. Extreme ecosystem instability suppressed tropical dinosaur dominance for 30 million years.Proc. Natl. Acad. Sci. USA. 2015; 112: 7909-7913https://doi.org/10.1073/pnas.1505252112Crossref PubMed Scopus (61) Google Scholar,10Bernardi M. Gianolla P. Petti F.M. Mietto P. Benton M.J. Dinosaur diversification linked with the Carnian pluvial episode.Nat. Commun. 2018; 9: 1499https://doi.org/10.1038/s41467-018-03996-1Crossref PubMed Scopus (87) Google Scholar,11Lovelace D.M. Hartman S.A. Mathewson P.D. Linzmeier B.J. Porter W.P. Modeling Dragons: using linked mechanistic physiological and microclimate models to explore environmental, physiological, and morphological constraints on the early evolution of dinosaurs.PLoS One. 2020; 15e0223872https://doi.org/10.1371/journal.pone.0223872Crossref Scopus (8) Google Scholar,12Mancuso A.C. Benavente C.A. Irmis R.B. Mundil R. Evidence for the Carnian pluvial episode in Gondwana: new multiproxy climate records and their bearing on early dinosaur diversification.Gondwana Res. 2020; 86: 104-125https://doi.org/10.1016/j.gr.2020.05.009Crossref Scopus (35) Google Scholar,13Mancuso A.C. Irmis R.B. Pedernera T.E. Gaetano L.C. Benavente C.A. Breeden III B.T. Paleoenvironmental and biotic changes in the late triassic of Argentina: testing hypotheses of abiotic forcing at the basin scale.Front. Earth Sci. 2022; 10https://doi.org/10.3389/feart.2022.883788Crossref PubMed Scopus (4) Google Scholar,14Kent D.V. Clemmensen L.B. Northward dispersal of dinosaurs from Gondwana to Greenland at the mid-Norian (215–212 Ma, Late Triassic) dip in atmospheric pCO2.Proc. Natl. Acad. Sci. USA. 2021; 118e2020778118https://doi.org/10.1073/pnas.2020778118Crossref Scopus (16) Google Scholar,15Griffin C.T. Wynd B.M. Munyikwa D. Broderick T.J. Zondo M. Tolan S. Langer M.C. Nesbitt S.J. Taruvinga H.R. Africa\'s oldest dinosaurs reveal early suppression of dinosaur distribution.Nature. 2022; 609: 313-319https://doi.org/10.1038/s41586-022-05133-xCrossref PubMed Scopus (4) Google Scholar,16Olsen P. Sha J. Fang Y. Chang C. Whiteside J.H. Kinney S. Sues H.-D. Kent D. Schaller M. Vajda V. Arctic ice and the ecological rise of the dinosaurs.Sci. Adv. 2022; 8eabo6342https://doi.org/10.1126/sciadv.abo6342Crossref Scopus (5) Google Scholar Here, we test this hypothesis and elucidate how climate influenced early dinosaur distribution by quantitatively examining changes in dinosaur and tetrapod "climatic niche space" across the Triassic-Jurassic boundary. Statistical analyses show that Late Triassic sauropodomorph dinosaurs occupied a more restricted climatic niche space than other tetrapods and dinosaurs, being excluded from the hottest, low-latitude climate zones. A subsequent, earliest Jurassic expansion of sauropodomorph geographic distribution is linked to the expansion of their preferred climatic conditions. Evolutionary model-fitting analyses provide evidence for an important evolutionary shift from cooler to warmer climatic niches during the origin of Sauropoda. These results are consistent with the hypothesis that global abundance of sauropodomorph dinosaurs was facilitated by climatic change and provide support for the key role of climate in the ascendancy of dinosaurs.',
+        'The development of technologies to slow climate change has been identified as a global imperative. Nonetheless, such ‘green’ technologies can potentially have negative impacts on biodiversity. We explored how climate change and the mining of lithium for green technologies influence surface water availability, primary productivity and the abundance of three threatened and economically important flamingo species in the ‘Lithium Triangle’ of the Chilean Andes. We combined climate and primary productivity data with remotely sensed measures of surface water levels and a 30-year dataset on flamingo abundance using structural equation modelling. We found that, regionally, flamingo abundance fluctuated dramatically from year-to-year in response to variation in surface water levels and primary productivity but did not exhibit any temporal trends. Locally, in the Salar de Atacama—where lithium mining is focused—we found that mining was negatively correlated with the abundance of two of the three flamingo species. These results suggest continued increases in lithium mining and declines in surface water could soon have dramatic effects on flamingo abundance across their range. Efforts to slow the expansion of mining and the impacts of climate change are, therefore, urgently needed to benefit local biodiversity and the local human economy that depends on it.',
+        'Rivers can abruptly shift pathways in rare events called avulsions, which cause devastating floods. The controls on avulsion locations are poorly understood as a result of sparse data on such features. We analyzed nearly 50 years of satellite imagery and documented 113 avulsions across the globe that indicate three distinct controls on avulsion location. Avulsions on fans coincide with valley-confinement change, whereas avulsions on deltas are primarily clustered within the backwater zone, indicating a control by spatial flow deceleration or acceleration during floods. However, 38% of avulsions on deltas occurred upstream of backwater effects. These events occurred in steep, sediment-rich rivers in tropical and desert environments. Our results indicate that avulsion location on deltas is set by the upstream extent of flood-driven erosion, which is typically limited to the backwater zone but can extend far upstream in steep, sediment-laden rivers. Our findings elucidate how avulsion hazards might respond to land use and climate change.',
+    ]
+)
+# [{'corpus_id': ..., 'score': ...}, {'corpus_id': ..., 'score': ...}, ...]
+```
+
+<!--
+### Direct Usage (Transformers)
+
+<details><summary>Click to see the direct usage in Transformers</summary>
+
+</details>
+-->
+
+<!--
+### Downstream Usage (Sentence Transformers)
+
+You can finetune this model on your own dataset.
+
+<details><summary>Click to expand</summary>
+
+</details>
+-->
+
+<!--
+### Out-of-Scope Use
+
+*List how the model may foreseeably be misused and address what users ought not to do with the model.*
+-->
+
+## Evaluation
+
+### Metrics
+
+#### Cross Encoder Reranking
+
+* Dataset: `climate-science-eval`
+* Evaluated with [<code>CrossEncoderRerankingEvaluator</code>](https://sbert.net/docs/package_reference/cross_encoder/evaluation.html#sentence_transformers.cross_encoder.evaluation.CrossEncoderRerankingEvaluator) with these parameters:
+  ```json
+  {
+      "at_k": 10,
+      "always_rerank_positives": true
+  }
+  ```
+
+| Metric      | Value                |
+|:------------|:---------------------|
+| map         | 0.6629 (+0.4483)     |
+| mrr@10      | 0.6554 (+0.4475)     |
+| **ndcg@10** | **0.7068 (+0.4669)** |
+
+<!--
+## Bias, Risks and Limitations
+
+*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
+-->
+
+<!--
+### Recommendations
+
+*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
+-->
+
+## Training Details
+
+### Training Dataset
+
+#### Unnamed Dataset
+
+* Size: 263,476 training samples
+* Columns: <code>query</code>, <code>answer</code>, and <code>label</code>
+* Approximate statistics based on the first 1000 samples:
+  |         | query                                                                                            | answer                                                                                              | label                                           |
+  |:--------|:-------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------|:------------------------------------------------|
+  | type    | string                                                                                           | string                                                                                              | int                                             |
+  | details | <ul><li>min: 55 characters</li><li>mean: 178.19 characters</li><li>max: 593 characters</li></ul> | <ul><li>min: 13 characters</li><li>mean: 1510.36 characters</li><li>max: 29945 characters</li></ul> | <ul><li>0: ~74.40%</li><li>1: ~25.60%</li></ul> |
+* Samples:
+  | query                                                                                                                                                                                                                            | answer                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   | label          |
+  |:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------|
+  | <code>The researchers say that with the right design a Mersey barrage has the potential to become a globally identifiable piece of architectural infrastructure - a 'hydropower landmark' boosting tourism to the region.</code> | <code>Currently there is renewed interest in harnessing the vast tidal resource to combat the twin challenges of climate change and energy security. However, within the UK no tidal barrage proposals have passed the development stage, this is due to a combination of high cost and environmental concerns. This paper demonstrates how a framework, such as the North West Hydro Resource Model can be applied to tidal barrages, with the Mersey barrage as a case study. The model materialised in order to provide developers with a tool to successfully identify the capacity of hydropower schemes in a specific location. A key feature of the resource model is the understanding that there is no single barrier to the utilisation of small hydropower but several obstacles, which together impede development. Thus, this paper contributes in part to a fully holistic treatment of tidal barrages, recognising that apart from energy generation, other environmental, societal and economic opportunities arise and must b...</code> | <code>1</code> |
+  | <code>The researchers say that with the right design a Mersey barrage has the potential to become a globally identifiable piece of architectural infrastructure - a 'hydropower landmark' boosting tourism to the region.</code> | <code>Rainbows contribute to human wellbeing by providing an inspiring connection to nature. Because the rainbow is an atmospheric optical phenomenon that results from the refraction of sunlight by rainwater droplets, changes in precipitation and cloud cover due to anthropogenic climate forcing will alter rainbow distribution. Yet, we lack a basic understanding of the current spatial distribution of rainbows and how climate change might alter this pattern. To assess how climate change might affect rainbow viewing opportunities, we developed a global database of crowd-sourced photographed rainbows, trained an empirical model of rainbow occurrence, and applied this model to present-day climate and three future climate scenarios. Results suggest that the average terrestrial location on Earth currently has 117 ± 71 days per year with conditions suitable for rainbows. By 2100, climate change is likely to generate a 4.0–4.9 % net increase in mean global annual rainbow-days (i.e., days with at leas...</code> | <code>0</code> |
+  | <code>The researchers say that with the right design a Mersey barrage has the potential to become a globally identifiable piece of architectural infrastructure - a 'hydropower landmark' boosting tourism to the region.</code> | <code>The ascendancy of dinosaurs to become dominant components of terrestrial ecosystems was a pivotal event in the history of life, yet the drivers of their early evolution and biodiversity are poorly understood.1Brusatte S.L. Benton M.J. Ruta M. Lloyd G.T. The first 50 Myr of dinosaur evolution: macroevolutionary pattern and morphological disparity.Biol. Lett. 2008; 4: 733-736https://doi.org/10.1098/rsbl.2008.0441Crossref PubMed Scopus (105) Google Scholar,2Irmis R.B. Evaluating hypotheses for the early diversification of dinosaurs.Earth Environ. Sci. Trans. R. Soc. Edinb. 2010; 101: 397-426https://doi.org/10.1017/S1755691011020068Crossref Scopus (94) Google Scholar,3Benton M.J. Forth J. Langer M.C. Models for the rise of the dinosaurs.Curr. Biol. 2014; 24: R87-R95https://doi.org/10.1016/j.cub.2013.11.063Abstract Full Text Full Text PDF PubMed Scopus (93) Google Scholar During their early diversification in the Late Triassic, dinosaurs were initially rare and geographically restricted, on...</code> | <code>0</code> |
+* Loss: [<code>BinaryCrossEntropyLoss</code>](https://sbert.net/docs/package_reference/cross_encoder/losses.html#binarycrossentropyloss) with these parameters:
+  ```json
+  {
+      "activation_fn": "torch.nn.modules.linear.Identity",
+      "pos_weight": 6
+  }
+  ```
+
+### Training Hyperparameters
+#### Non-Default Hyperparameters
+
+- `eval_strategy`: steps
+- `per_device_train_batch_size`: 16
+- `per_device_eval_batch_size`: 16
+- `learning_rate`: 2e-05
+- `warmup_ratio`: 0.1
+- `fp16`: True
+- `dataloader_num_workers`: 4
+- `load_best_model_at_end`: True
+
+#### All Hyperparameters
+<details><summary>Click to expand</summary>
+
+- `overwrite_output_dir`: False
+- `do_predict`: False
+- `eval_strategy`: steps
+- `prediction_loss_only`: True
+- `per_device_train_batch_size`: 16
+- `per_device_eval_batch_size`: 16
+- `per_gpu_train_batch_size`: None
+- `per_gpu_eval_batch_size`: None
+- `gradient_accumulation_steps`: 1
+- `eval_accumulation_steps`: None
+- `torch_empty_cache_steps`: None
+- `learning_rate`: 2e-05
+- `weight_decay`: 0.0
+- `adam_beta1`: 0.9
+- `adam_beta2`: 0.999
+- `adam_epsilon`: 1e-08
+- `max_grad_norm`: 1.0
+- `num_train_epochs`: 3
+- `max_steps`: -1
+- `lr_scheduler_type`: linear
+- `lr_scheduler_kwargs`: {}
+- `warmup_ratio`: 0.1
+- `warmup_steps`: 0
+- `log_level`: passive
+- `log_level_replica`: warning
+- `log_on_each_node`: True
+- `logging_nan_inf_filter`: True
+- `save_safetensors`: True
+- `save_on_each_node`: False
+- `save_only_model`: False
+- `restore_callback_states_from_checkpoint`: False
+- `no_cuda`: False
+- `use_cpu`: False
+- `use_mps_device`: False
+- `seed`: 42
+- `data_seed`: None
+- `jit_mode_eval`: False
+- `use_ipex`: False
+- `bf16`: False
+- `fp16`: True
+- `fp16_opt_level`: O1
+- `half_precision_backend`: auto
+- `bf16_full_eval`: False
+- `fp16_full_eval`: False
+- `tf32`: None
+- `local_rank`: 0
+- `ddp_backend`: None
+- `tpu_num_cores`: None
+- `tpu_metrics_debug`: False
+- `debug`: []
+- `dataloader_drop_last`: False
+- `dataloader_num_workers`: 4
+- `dataloader_prefetch_factor`: None
+- `past_index`: -1
+- `disable_tqdm`: False
+- `remove_unused_columns`: True
+- `label_names`: None
+- `load_best_model_at_end`: True
+- `ignore_data_skip`: False
+- `fsdp`: []
+- `fsdp_min_num_params`: 0
+- `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
+- `tp_size`: 0
+- `fsdp_transformer_layer_cls_to_wrap`: None
+- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
+- `deepspeed`: None
+- `label_smoothing_factor`: 0.0
+- `optim`: adamw_torch
+- `optim_args`: None
+- `adafactor`: False
+- `group_by_length`: False
+- `length_column_name`: length
+- `ddp_find_unused_parameters`: None
+- `ddp_bucket_cap_mb`: None
+- `ddp_broadcast_buffers`: False
+- `dataloader_pin_memory`: True
+- `dataloader_persistent_workers`: False
+- `skip_memory_metrics`: True
+- `use_legacy_prediction_loop`: False
+- `push_to_hub`: False
+- `resume_from_checkpoint`: None
+- `hub_model_id`: None
+- `hub_strategy`: every_save
+- `hub_private_repo`: None
+- `hub_always_push`: False
+- `gradient_checkpointing`: False
+- `gradient_checkpointing_kwargs`: None
+- `include_inputs_for_metrics`: False
+- `include_for_metrics`: []
+- `eval_do_concat_batches`: True
+- `fp16_backend`: auto
+- `push_to_hub_model_id`: None
+- `push_to_hub_organization`: None
+- `mp_parameters`: 
+- `auto_find_batch_size`: False
+- `full_determinism`: False
+- `torchdynamo`: None
+- `ray_scope`: last
+- `ddp_timeout`: 1800
+- `torch_compile`: False
+- `torch_compile_backend`: None
+- `torch_compile_mode`: None
+- `include_tokens_per_second`: False
+- `include_num_input_tokens_seen`: False
+- `neftune_noise_alpha`: None
+- `optim_target_modules`: None
+- `batch_eval_metrics`: False
+- `eval_on_start`: False
+- `use_liger_kernel`: False
+- `eval_use_gather_object`: False
+- `average_tokens_across_devices`: False
+- `prompts`: None
+- `batch_sampler`: batch_sampler
+- `multi_dataset_batch_sampler`: proportional
+
+</details>
+
+### Training Logs
+<details><summary>Click to expand</summary>
+
+| Epoch      | Step      | Training Loss | climate-science-eval_ndcg@10 |
+|:----------:|:---------:|:-------------:|:----------------------------:|
+| 0.0001     | 1         | 6.4826        | -                            |
+| 0.0061     | 100       | 6.3516        | -                            |
+| 0.0121     | 200       | 5.1792        | -                            |
+| 0.0182     | 300       | 2.9628        | -                            |
+| 0.0243     | 400       | 1.8946        | -                            |
+| 0.0304     | 500       | 1.3992        | -                            |
+| 0.0364     | 600       | 1.4469        | -                            |
+| 0.0425     | 700       | 1.1841        | -                            |
+| 0.0486     | 800       | 0.9967        | -                            |
+| 0.0547     | 900       | 0.9914        | -                            |
+| 0.0607     | 1000      | 0.7138        | 0.6113 (+0.3713)             |
+| 0.0668     | 1100      | 0.6944        | -                            |
+| 0.0729     | 1200      | 0.7374        | -                            |
+| 0.0789     | 1300      | 0.7249        | -                            |
+| 0.0850     | 1400      | 0.8826        | -                            |
+| 0.0911     | 1500      | 0.6886        | -                            |
+| 0.0972     | 1600      | 0.8185        | -                            |
+| 0.1032     | 1700      | 0.6946        | -                            |
+| 0.1093     | 1800      | 0.7231        | -                            |
+| 0.1154     | 1900      | 0.668         | -                            |
+| 0.1214     | 2000      | 0.6434        | 0.6325 (+0.3926)             |
+| 0.1275     | 2100      | 0.7417        | -                            |
+| 0.1336     | 2200      | 0.6777        | -                            |
+| 0.1397     | 2300      | 0.779         | -                            |
+| 0.1457     | 2400      | 0.6876        | -                            |
+| 0.1518     | 2500      | 0.6619        | -                            |
+| 0.1579     | 2600      | 0.6626        | -                            |
+| 0.1640     | 2700      | 0.7394        | -                            |
+| 0.1700     | 2800      | 0.6654        | -                            |
+| 0.1761     | 2900      | 0.6026        | -                            |
+| 0.1822     | 3000      | 0.6838        | 0.6417 (+0.4018)             |
+| 0.1882     | 3100      | 0.6423        | -                            |
+| 0.1943     | 3200      | 0.6559        | -                            |
+| 0.2004     | 3300      | 0.6097        | -                            |
+| 0.2065     | 3400      | 0.6564        | -                            |
+| 0.2125     | 3500      | 0.6912        | -                            |
+| 0.2186     | 3600      | 0.6183        | -                            |
+| 0.2247     | 3700      | 0.5585        | -                            |
+| 0.2308     | 3800      | 0.6748        | -                            |
+| 0.2368     | 3900      | 0.6165        | -                            |
+| 0.2429     | 4000      | 0.6358        | 0.6529 (+0.4130)             |
+| 0.2490     | 4100      | 0.6473        | -                            |
+| 0.2550     | 4200      | 0.6766        | -                            |
+| 0.2611     | 4300      | 0.6603        | -                            |
+| 0.2672     | 4400      | 0.5778        | -                            |
+| 0.2733     | 4500      | 0.6732        | -                            |
+| 0.2793     | 4600      | 0.605         | -                            |
+| 0.2854     | 4700      | 0.6943        | -                            |
+| 0.2915     | 4800      | 0.5776        | -                            |
+| 0.2975     | 4900      | 0.706         | -                            |
+| 0.3036     | 5000      | 0.5758        | 0.6559 (+0.4160)             |
+| 0.3097     | 5100      | 0.6596        | -                            |
+| 0.3158     | 5200      | 0.6466        | -                            |
+| 0.3218     | 5300      | 0.6116        | -                            |
+| 0.3279     | 5400      | 0.5654        | -                            |
+| 0.3340     | 5500      | 0.643         | -                            |
+| 0.3401     | 5600      | 0.7281        | -                            |
+| 0.3461     | 5700      | 0.6295        | -                            |
+| 0.3522     | 5800      | 0.6555        | -                            |
+| 0.3583     | 5900      | 0.6671        | -                            |
+| 0.3643     | 6000      | 0.6647        | 0.6537 (+0.4138)             |
+| 0.3704     | 6100      | 0.5458        | -                            |
+| 0.3765     | 6200      | 0.6279        | -                            |
+| 0.3826     | 6300      | 0.6575        | -                            |
+| 0.3886     | 6400      | 0.6206        | -                            |
+| 0.3947     | 6500      | 0.5802        | -                            |
+| 0.4008     | 6600      | 0.7117        | -                            |
+| 0.4068     | 6700      | 0.589         | -                            |
+| 0.4129     | 6800      | 0.6245        | -                            |
+| 0.4190     | 6900      | 0.5346        | -                            |
+| 0.4251     | 7000      | 0.7323        | 0.6559 (+0.4160)             |
+| 0.4311     | 7100      | 0.5407        | -                            |
+| 0.4372     | 7200      | 0.53          | -                            |
+| 0.4433     | 7300      | 0.5586        | -                            |
+| 0.4494     | 7400      | 0.6219        | -                            |
+| 0.4554     | 7500      | 0.6396        | -                            |
+| 0.4615     | 7600      | 0.54          | -                            |
+| 0.4676     | 7700      | 0.6284        | -                            |
+| 0.4736     | 7800      | 0.6021        | -                            |
+| 0.4797     | 7900      | 0.6326        | -                            |
+| 0.4858     | 8000      | 0.6375        | 0.6691 (+0.4291)             |
+| 0.4919     | 8100      | 0.5402        | -                            |
+| 0.4979     | 8200      | 0.582         | -                            |
+| 0.5040     | 8300      | 0.5382        | -                            |
+| 0.5101     | 8400      | 0.581         | -                            |
+| 0.5162     | 8500      | 0.6062        | -                            |
+| 0.5222     | 8600      | 0.5804        | -                            |
+| 0.5283     | 8700      | 0.6233        | -                            |
+| 0.5344     | 8800      | 0.5813        | -                            |
+| 0.5404     | 8900      | 0.5619        | -                            |
+| 0.5465     | 9000      | 0.5328        | 0.6694 (+0.4295)             |
+| 0.5526     | 9100      | 0.5371        | -                            |
+| 0.5587     | 9200      | 0.6534        | -                            |
+| 0.5647     | 9300      | 0.5395        | -                            |
+| 0.5708     | 9400      | 0.577         | -                            |
+| 0.5769     | 9500      | 0.5936        | -                            |
+| 0.5829     | 9600      | 0.5947        | -                            |
+| 0.5890     | 9700      | 0.5806        | -                            |
+| 0.5951     | 9800      | 0.6236        | -                            |
+| 0.6012     | 9900      | 0.6087        | -                            |
+| 0.6072     | 10000     | 0.5466        | 0.6712 (+0.4313)             |
+| 0.6133     | 10100     | 0.6824        | -                            |
+| 0.6194     | 10200     | 0.5657        | -                            |
+| 0.6255     | 10300     | 0.5772        | -                            |
+| 0.6315     | 10400     | 0.6068        | -                            |
+| 0.6376     | 10500     | 0.4815        | -                            |
+| 0.6437     | 10600     | 0.527         | -                            |
+| 0.6497     | 10700     | 0.6041        | -                            |
+| 0.6558     | 10800     | 0.5542        | -                            |
+| 0.6619     | 10900     | 0.5846        | -                            |
+| 0.6680     | 11000     | 0.5559        | 0.6683 (+0.4284)             |
+| 0.6740     | 11100     | 0.6235        | -                            |
+| 0.6801     | 11200     | 0.581         | -                            |
+| 0.6862     | 11300     | 0.5931        | -                            |
+| 0.6923     | 11400     | 0.532         | -                            |
+| 0.6983     | 11500     | 0.5832        | -                            |
+| 0.7044     | 11600     | 0.4815        | -                            |
+| 0.7105     | 11700     | 0.7507        | -                            |
+| 0.7165     | 11800     | 0.555         | -                            |
+| 0.7226     | 11900     | 0.585         | -                            |
+| 0.7287     | 12000     | 0.6486        | 0.6711 (+0.4311)             |
+| 0.7348     | 12100     | 0.6077        | -                            |
+| 0.7408     | 12200     | 0.5116        | -                            |
+| 0.7469     | 12300     | 0.6163        | -                            |
+| 0.7530     | 12400     | 0.6205        | -                            |
+| 0.7590     | 12500     | 0.5086        | -                            |
+| 0.7651     | 12600     | 0.5544        | -                            |
+| 0.7712     | 12700     | 0.4743        | -                            |
+| 0.7773     | 12800     | 0.5854        | -                            |
+| 0.7833     | 12900     | 0.5681        | -                            |
+| 0.7894     | 13000     | 0.6179        | 0.6760 (+0.4360)             |
+| 0.7955     | 13100     | 0.5958        | -                            |
+| 0.8016     | 13200     | 0.5162        | -                            |
+| 0.8076     | 13300     | 0.609         | -                            |
+| 0.8137     | 13400     | 0.4877        | -                            |
+| 0.8198     | 13500     | 0.6157        | -                            |
+| 0.8258     | 13600     | 0.5638        | -                            |
+| 0.8319     | 13700     | 0.5049        | -                            |
+| 0.8380     | 13800     | 0.7226        | -                            |
+| 0.8441     | 13900     | 0.515         | -                            |
+| 0.8501     | 14000     | 0.5564        | 0.6822 (+0.4423)             |
+| 0.8562     | 14100     | 0.5618        | -                            |
+| 0.8623     | 14200     | 0.5448        | -                            |
+| 0.8684     | 14300     | 0.5693        | -                            |
+| 0.8744     | 14400     | 0.6417        | -                            |
+| 0.8805     | 14500     | 0.5609        | -                            |
+| 0.8866     | 14600     | 0.6033        | -                            |
+| 0.8926     | 14700     | 0.6355        | -                            |
+| 0.8987     | 14800     | 0.5322        | -                            |
+| 0.9048     | 14900     | 0.519         | -                            |
+| 0.9109     | 15000     | 0.5662        | 0.6764 (+0.4365)             |
+| 0.9169     | 15100     | 0.593         | -                            |
+| 0.9230     | 15200     | 0.6004        | -                            |
+| 0.9291     | 15300     | 0.5673        | -                            |
+| 0.9351     | 15400     | 0.5142        | -                            |
+| 0.9412     | 15500     | 0.5859        | -                            |
+| 0.9473     | 15600     | 0.6421        | -                            |
+| 0.9534     | 15700     | 0.4822        | -                            |
+| 0.9594     | 15800     | 0.6082        | -                            |
+| 0.9655     | 15900     | 0.5373        | -                            |
+| 0.9716     | 16000     | 0.6102        | 0.6729 (+0.4330)             |
+| 0.9777     | 16100     | 0.5109        | -                            |
+| 0.9837     | 16200     | 0.6156        | -                            |
+| 0.9898     | 16300     | 0.6408        | -                            |
+| 0.9959     | 16400     | 0.5031        | -                            |
+| 1.0019     | 16500     | 0.4652        | -                            |
+| 1.0080     | 16600     | 0.3893        | -                            |
+| 1.0141     | 16700     | 0.6276        | -                            |
+| 1.0202     | 16800     | 0.5526        | -                            |
+| 1.0262     | 16900     | 0.551         | -                            |
+| 1.0323     | 17000     | 0.5066        | 0.6832 (+0.4432)             |
+| 1.0384     | 17100     | 0.5074        | -                            |
+| 1.0444     | 17200     | 0.48          | -                            |
+| 1.0505     | 17300     | 0.6073        | -                            |
+| 1.0566     | 17400     | 0.485         | -                            |
+| 1.0627     | 17500     | 0.4927        | -                            |
+| 1.0687     | 17600     | 0.597         | -                            |
+| 1.0748     | 17700     | 0.4376        | -                            |
+| 1.0809     | 17800     | 0.4935        | -                            |
+| 1.0870     | 17900     | 0.5702        | -                            |
+| 1.0930     | 18000     | 0.4482        | 0.6825 (+0.4426)             |
+| 1.0991     | 18100     | 0.5183        | -                            |
+| 1.1052     | 18200     | 0.4593        | -                            |
+| 1.1112     | 18300     | 0.4775        | -                            |
+| 1.1173     | 18400     | 0.5831        | -                            |
+| 1.1234     | 18500     | 0.4942        | -                            |
+| 1.1295     | 18600     | 0.5684        | -                            |
+| 1.1355     | 18700     | 0.5214        | -                            |
+| 1.1416     | 18800     | 0.5292        | -                            |
+| 1.1477     | 18900     | 0.5163        | -                            |
+| 1.1538     | 19000     | 0.5305        | 0.6868 (+0.4469)             |
+| 1.1598     | 19100     | 0.4507        | -                            |
+| 1.1659     | 19200     | 0.4699        | -                            |
+| 1.1720     | 19300     | 0.4532        | -                            |
+| 1.1780     | 19400     | 0.4853        | -                            |
+| 1.1841     | 19500     | 0.5169        | -                            |
+| 1.1902     | 19600     | 0.5927        | -                            |
+| 1.1963     | 19700     | 0.5777        | -                            |
+| 1.2023     | 19800     | 0.5041        | -                            |
+| 1.2084     | 19900     | 0.5309        | -                            |
+| 1.2145     | 20000     | 0.4426        | 0.6809 (+0.4410)             |
+| 1.2205     | 20100     | 0.54          | -                            |
+| 1.2266     | 20200     | 0.5692        | -                            |
+| 1.2327     | 20300     | 0.5004        | -                            |
+| 1.2388     | 20400     | 0.5044        | -                            |
+| 1.2448     | 20500     | 0.4574        | -                            |
+| 1.2509     | 20600     | 0.6132        | -                            |
+| 1.2570     | 20700     | 0.4477        | -                            |
+| 1.2631     | 20800     | 0.4805        | -                            |
+| 1.2691     | 20900     | 0.6127        | -                            |
+| 1.2752     | 21000     | 0.4349        | 0.6914 (+0.4515)             |
+| 1.2813     | 21100     | 0.6595        | -                            |
+| 1.2873     | 21200     | 0.5234        | -                            |
+| 1.2934     | 21300     | 0.4525        | -                            |
+| 1.2995     | 21400     | 0.3841        | -                            |
+| 1.3056     | 21500     | 0.5215        | -                            |
+| 1.3116     | 21600     | 0.6187        | -                            |
+| 1.3177     | 21700     | 0.4491        | -                            |
+| 1.3238     | 21800     | 0.629         | -                            |
+| 1.3299     | 21900     | 0.6247        | -                            |
+| 1.3359     | 22000     | 0.461         | 0.6858 (+0.4459)             |
+| 1.3420     | 22100     | 0.5351        | -                            |
+| 1.3481     | 22200     | 0.4602        | -                            |
+| 1.3541     | 22300     | 0.4915        | -                            |
+| 1.3602     | 22400     | 0.5056        | -                            |
+| 1.3663     | 22500     | 0.4976        | -                            |
+| 1.3724     | 22600     | 0.4983        | -                            |
+| 1.3784     | 22700     | 0.6245        | -                            |
+| 1.3845     | 22800     | 0.5009        | -                            |
+| 1.3906     | 22900     | 0.4268        | -                            |
+| 1.3966     | 23000     | 0.5552        | 0.6860 (+0.4461)             |
+| 1.4027     | 23100     | 0.5136        | -                            |
+| 1.4088     | 23200     | 0.5308        | -                            |
+| 1.4149     | 23300     | 0.4796        | -                            |
+| 1.4209     | 23400     | 0.5315        | -                            |
+| 1.4270     | 23500     | 0.4997        | -                            |
+| 1.4331     | 23600     | 0.457         | -                            |
+| 1.4392     | 23700     | 0.5553        | -                            |
+| 1.4452     | 23800     | 0.5262        | -                            |
+| 1.4513     | 23900     | 0.3976        | -                            |
+| 1.4574     | 24000     | 0.4542        | 0.6929 (+0.4530)             |
+| 1.4634     | 24100     | 0.5882        | -                            |
+| 1.4695     | 24200     | 0.4332        | -                            |
+| 1.4756     | 24300     | 0.4206        | -                            |
+| 1.4817     | 24400     | 0.5621        | -                            |
+| 1.4877     | 24500     | 0.5347        | -                            |
+| 1.4938     | 24600     | 0.3999        | -                            |
+| 1.4999     | 24700     | 0.4689        | -                            |
+| 1.5060     | 24800     | 0.4581        | -                            |
+| 1.5120     | 24900     | 0.547         | -                            |
+| 1.5181     | 25000     | 0.476         | 0.6919 (+0.4520)             |
+| 1.5242     | 25100     | 0.4884        | -                            |
+| 1.5302     | 25200     | 0.4404        | -                            |
+| 1.5363     | 25300     | 0.4938        | -                            |
+| 1.5424     | 25400     | 0.5362        | -                            |
+| 1.5485     | 25500     | 0.5063        | -                            |
+| 1.5545     | 25600     | 0.5653        | -                            |
+| 1.5606     | 25700     | 0.4717        | -                            |
+| 1.5667     | 25800     | 0.4901        | -                            |
+| 1.5727     | 25900     | 0.5102        | -                            |
+| 1.5788     | 26000     | 0.5277        | 0.6878 (+0.4479)             |
+| 1.5849     | 26100     | 0.496         | -                            |
+| 1.5910     | 26200     | 0.553         | -                            |
+| 1.5970     | 26300     | 0.5712        | -                            |
+| 1.6031     | 26400     | 0.5246        | -                            |
+| 1.6092     | 26500     | 0.5805        | -                            |
+| 1.6153     | 26600     | 0.5651        | -                            |
+| 1.6213     | 26700     | 0.6139        | -                            |
+| 1.6274     | 26800     | 0.4898        | -                            |
+| 1.6335     | 26900     | 0.4464        | -                            |
+| 1.6395     | 27000     | 0.479         | 0.6926 (+0.4527)             |
+| 1.6456     | 27100     | 0.5201        | -                            |
+| 1.6517     | 27200     | 0.3981        | -                            |
+| 1.6578     | 27300     | 0.5541        | -                            |
+| 1.6638     | 27400     | 0.5546        | -                            |
+| 1.6699     | 27500     | 0.4874        | -                            |
+| 1.6760     | 27600     | 0.5388        | -                            |
+| 1.6821     | 27700     | 0.4642        | -                            |
+| 1.6881     | 27800     | 0.5017        | -                            |
+| 1.6942     | 27900     | 0.4948        | -                            |
+| 1.7003     | 28000     | 0.5065        | 0.6970 (+0.4571)             |
+| 1.7063     | 28100     | 0.5501        | -                            |
+| 1.7124     | 28200     | 0.3532        | -                            |
+| 1.7185     | 28300     | 0.5828        | -                            |
+| 1.7246     | 28400     | 0.4659        | -                            |
+| 1.7306     | 28500     | 0.5192        | -                            |
+| 1.7367     | 28600     | 0.4208        | -                            |
+| 1.7428     | 28700     | 0.5869        | -                            |
+| 1.7488     | 28800     | 0.5452        | -                            |
+| 1.7549     | 28900     | 0.5222        | -                            |
+| 1.7610     | 29000     | 0.5656        | 0.6987 (+0.4587)             |
+| 1.7671     | 29100     | 0.5486        | -                            |
+| 1.7731     | 29200     | 0.4706        | -                            |
+| 1.7792     | 29300     | 0.5038        | -                            |
+| 1.7853     | 29400     | 0.4439        | -                            |
+| 1.7914     | 29500     | 0.5442        | -                            |
+| 1.7974     | 29600     | 0.4777        | -                            |
+| 1.8035     | 29700     | 0.5777        | -                            |
+| 1.8096     | 29800     | 0.4981        | -                            |
+| 1.8156     | 29900     | 0.4757        | -                            |
+| 1.8217     | 30000     | 0.498         | 0.6971 (+0.4572)             |
+| 1.8278     | 30100     | 0.5251        | -                            |
+| 1.8339     | 30200     | 0.4121        | -                            |
+| 1.8399     | 30300     | 0.5471        | -                            |
+| 1.8460     | 30400     | 0.4772        | -                            |
+| 1.8521     | 30500     | 0.4986        | -                            |
+| 1.8581     | 30600     | 0.5598        | -                            |
+| 1.8642     | 30700     | 0.4857        | -                            |
+| 1.8703     | 30800     | 0.3509        | -                            |
+| 1.8764     | 30900     | 0.5719        | -                            |
+| 1.8824     | 31000     | 0.5183        | 0.7000 (+0.4600)             |
+| 1.8885     | 31100     | 0.3952        | -                            |
+| 1.8946     | 31200     | 0.5221        | -                            |
+| 1.9007     | 31300     | 0.4777        | -                            |
+| 1.9067     | 31400     | 0.4371        | -                            |
+| 1.9128     | 31500     | 0.5726        | -                            |
+| 1.9189     | 31600     | 0.5451        | -                            |
+| 1.9249     | 31700     | 0.5352        | -                            |
+| 1.9310     | 31800     | 0.4411        | -                            |
+| 1.9371     | 31900     | 0.4589        | -                            |
+| 1.9432     | 32000     | 0.4623        | 0.6922 (+0.4523)             |
+| 1.9492     | 32100     | 0.4656        | -                            |
+| 1.9553     | 32200     | 0.4595        | -                            |
+| 1.9614     | 32300     | 0.5686        | -                            |
+| 1.9675     | 32400     | 0.3952        | -                            |
+| 1.9735     | 32500     | 0.3992        | -                            |
+| 1.9796     | 32600     | 0.4397        | -                            |
+| 1.9857     | 32700     | 0.5823        | -                            |
+| 1.9917     | 32800     | 0.3741        | -                            |
+| 1.9978     | 32900     | 0.5914        | -                            |
+| 2.0039     | 33000     | 0.3066        | 0.7022 (+0.4623)             |
+| 2.0100     | 33100     | 0.3759        | -                            |
+| 2.0160     | 33200     | 0.4164        | -                            |
+| 2.0221     | 33300     | 0.3911        | -                            |
+| 2.0282     | 33400     | 0.4269        | -                            |
+| 2.0342     | 33500     | 0.397         | -                            |
+| 2.0403     | 33600     | 0.378         | -                            |
+| 2.0464     | 33700     | 0.5975        | -                            |
+| 2.0525     | 33800     | 0.4485        | -                            |
+| 2.0585     | 33900     | 0.3636        | -                            |
+| 2.0646     | 34000     | 0.3081        | 0.7009 (+0.4610)             |
+| 2.0707     | 34100     | 0.4204        | -                            |
+| 2.0768     | 34200     | 0.4379        | -                            |
+| 2.0828     | 34300     | 0.4619        | -                            |
+| 2.0889     | 34400     | 0.3795        | -                            |
+| 2.0950     | 34500     | 0.4356        | -                            |
+| 2.1010     | 34600     | 0.4095        | -                            |
+| 2.1071     | 34700     | 0.454         | -                            |
+| 2.1132     | 34800     | 0.4248        | -                            |
+| 2.1193     | 34900     | 0.3987        | -                            |
+| 2.1253     | 35000     | 0.4074        | 0.6997 (+0.4598)             |
+| 2.1314     | 35100     | 0.4302        | -                            |
+| 2.1375     | 35200     | 0.4459        | -                            |
+| 2.1436     | 35300     | 0.4961        | -                            |
+| 2.1496     | 35400     | 0.4565        | -                            |
+| 2.1557     | 35500     | 0.438         | -                            |
+| 2.1618     | 35600     | 0.4256        | -                            |
+| 2.1678     | 35700     | 0.4943        | -                            |
+| 2.1739     | 35800     | 0.4378        | -                            |
+| 2.1800     | 35900     | 0.4059        | -                            |
+| 2.1861     | 36000     | 0.4706        | 0.7022 (+0.4623)             |
+| 2.1921     | 36100     | 0.4848        | -                            |
+| 2.1982     | 36200     | 0.5028        | -                            |
+| 2.2043     | 36300     | 0.4847        | -                            |
+| 2.2103     | 36400     | 0.3933        | -                            |
+| 2.2164     | 36500     | 0.4298        | -                            |
+| 2.2225     | 36600     | 0.5339        | -                            |
+| 2.2286     | 36700     | 0.3225        | -                            |
+| 2.2346     | 36800     | 0.3906        | -                            |
+| 2.2407     | 36900     | 0.3294        | -                            |
+| 2.2468     | 37000     | 0.4511        | 0.6971 (+0.4572)             |
+| 2.2529     | 37100     | 0.3817        | -                            |
+| 2.2589     | 37200     | 0.4822        | -                            |
+| 2.2650     | 37300     | 0.3975        | -                            |
+| 2.2711     | 37400     | 0.4482        | -                            |
+| 2.2771     | 37500     | 0.3826        | -                            |
+| 2.2832     | 37600     | 0.5013        | -                            |
+| 2.2893     | 37700     | 0.3956        | -                            |
+| 2.2954     | 37800     | 0.438         | -                            |
+| 2.3014     | 37900     | 0.5253        | -                            |
+| 2.3075     | 38000     | 0.3576        | 0.7000 (+0.4601)             |
+| 2.3136     | 38100     | 0.4061        | -                            |
+| 2.3197     | 38200     | 0.456         | -                            |
+| 2.3257     | 38300     | 0.5257        | -                            |
+| 2.3318     | 38400     | 0.5533        | -                            |
+| 2.3379     | 38500     | 0.4898        | -                            |
+| 2.3439     | 38600     | 0.3854        | -                            |
+| 2.3500     | 38700     | 0.4025        | -                            |
+| 2.3561     | 38800     | 0.5514        | -                            |
+| 2.3622     | 38900     | 0.441         | -                            |
+| 2.3682     | 39000     | 0.4563        | 0.7003 (+0.4603)             |
+| 2.3743     | 39100     | 0.436         | -                            |
+| 2.3804     | 39200     | 0.4162        | -                            |
+| 2.3864     | 39300     | 0.5437        | -                            |
+| 2.3925     | 39400     | 0.4212        | -                            |
+| 2.3986     | 39500     | 0.3891        | -                            |
+| 2.4047     | 39600     | 0.3907        | -                            |
+| 2.4107     | 39700     | 0.4422        | -                            |
+| 2.4168     | 39800     | 0.4499        | -                            |
+| 2.4229     | 39900     | 0.4889        | -                            |
+| 2.4290     | 40000     | 0.4213        | 0.7018 (+0.4619)             |
+| 2.4350     | 40100     | 0.4689        | -                            |
+| 2.4411     | 40200     | 0.4344        | -                            |
+| 2.4472     | 40300     | 0.4739        | -                            |
+| 2.4532     | 40400     | 0.4998        | -                            |
+| 2.4593     | 40500     | 0.4831        | -                            |
+| 2.4654     | 40600     | 0.4539        | -                            |
+| 2.4715     | 40700     | 0.4089        | -                            |
+| 2.4775     | 40800     | 0.3621        | -                            |
+| 2.4836     | 40900     | 0.4391        | -                            |
+| 2.4897     | 41000     | 0.4505        | 0.7044 (+0.4645)             |
+| 2.4957     | 41100     | 0.5392        | -                            |
+| 2.5018     | 41200     | 0.3973        | -                            |
+| 2.5079     | 41300     | 0.4245        | -                            |
+| 2.5140     | 41400     | 0.3979        | -                            |
+| 2.5200     | 41500     | 0.4979        | -                            |
+| 2.5261     | 41600     | 0.4346        | -                            |
+| 2.5322     | 41700     | 0.5294        | -                            |
+| 2.5383     | 41800     | 0.2816        | -                            |
+| 2.5443     | 41900     | 0.4917        | -                            |
+| **2.5504** | **42000** | **0.5214**    | **0.7068 (+0.4669)**         |
+| 2.5565     | 42100     | 0.4735        | -                            |
+| 2.5625     | 42200     | 0.3989        | -                            |
+| 2.5686     | 42300     | 0.397         | -                            |
+| 2.5747     | 42400     | 0.4202        | -                            |
+| 2.5808     | 42500     | 0.3813        | -                            |
+| 2.5868     | 42600     | 0.3742        | -                            |
+| 2.5929     | 42700     | 0.3593        | -                            |
+| 2.5990     | 42800     | 0.4132        | -                            |
+| 2.6051     | 42900     | 0.4089        | -                            |
+| 2.6111     | 43000     | 0.555         | 0.7057 (+0.4658)             |
+| 2.6172     | 43100     | 0.3949        | -                            |
+| 2.6233     | 43200     | 0.3216        | -                            |
+| 2.6293     | 43300     | 0.4265        | -                            |
+| 2.6354     | 43400     | 0.4529        | -                            |
+| 2.6415     | 43500     | 0.5047        | -                            |
+| 2.6476     | 43600     | 0.5522        | -                            |
+| 2.6536     | 43700     | 0.4635        | -                            |
+| 2.6597     | 43800     | 0.3012        | -                            |
+| 2.6658     | 43900     | 0.3738        | -                            |
+| 2.6718     | 44000     | 0.4507        | 0.7040 (+0.4641)             |
+| 2.6779     | 44100     | 0.4097        | -                            |
+| 2.6840     | 44200     | 0.3425        | -                            |
+| 2.6901     | 44300     | 0.3934        | -                            |
+| 2.6961     | 44400     | 0.507         | -                            |
+| 2.7022     | 44500     | 0.4207        | -                            |
+| 2.7083     | 44600     | 0.3949        | -                            |
+| 2.7144     | 44700     | 0.4073        | -                            |
+| 2.7204     | 44800     | 0.547         | -                            |
+| 2.7265     | 44900     | 0.5141        | -                            |
+| 2.7326     | 45000     | 0.3943        | 0.7045 (+0.4646)             |
+| 2.7386     | 45100     | 0.4786        | -                            |
+| 2.7447     | 45200     | 0.4747        | -                            |
+| 2.7508     | 45300     | 0.4123        | -                            |
+| 2.7569     | 45400     | 0.5173        | -                            |
+| 2.7629     | 45500     | 0.3601        | -                            |
+| 2.7690     | 45600     | 0.4944        | -                            |
+| 2.7751     | 45700     | 0.3822        | -                            |
+| 2.7812     | 45800     | 0.5818        | -                            |
+| 2.7872     | 45900     | 0.3503        | -                            |
+| 2.7933     | 46000     | 0.4496        | 0.7039 (+0.4640)             |
+| 2.7994     | 46100     | 0.4341        | -                            |
+| 2.8054     | 46200     | 0.5068        | -                            |
+| 2.8115     | 46300     | 0.4157        | -                            |
+| 2.8176     | 46400     | 0.5226        | -                            |
+| 2.8237     | 46500     | 0.4521        | -                            |
+| 2.8297     | 46600     | 0.3809        | -                            |
+| 2.8358     | 46700     | 0.4364        | -                            |
+| 2.8419     | 46800     | 0.3719        | -                            |
+| 2.8479     | 46900     | 0.4458        | -                            |
+| 2.8540     | 47000     | 0.3888        | 0.7036 (+0.4636)             |
+| 2.8601     | 47100     | 0.3331        | -                            |
+| 2.8662     | 47200     | 0.4155        | -                            |
+| 2.8722     | 47300     | 0.4436        | -                            |
+| 2.8783     | 47400     | 0.4629        | -                            |
+| 2.8844     | 47500     | 0.4362        | -                            |
+| 2.8905     | 47600     | 0.551         | -                            |
+| 2.8965     | 47700     | 0.4062        | -                            |
+| 2.9026     | 47800     | 0.4636        | -                            |
+| 2.9087     | 47900     | 0.2969        | -                            |
+| 2.9147     | 48000     | 0.4171        | 0.7035 (+0.4636)             |
+| 2.9208     | 48100     | 0.499         | -                            |
+| 2.9269     | 48200     | 0.4536        | -                            |
+| 2.9330     | 48300     | 0.4865        | -                            |
+| 2.9390     | 48400     | 0.4162        | -                            |
+| 2.9451     | 48500     | 0.4401        | -                            |
+| 2.9512     | 48600     | 0.4846        | -                            |
+| 2.9573     | 48700     | 0.3991        | -                            |
+| 2.9633     | 48800     | 0.3574        | -                            |
+| 2.9694     | 48900     | 0.4327        | -                            |
+| 2.9755     | 49000     | 0.3185        | 0.7040 (+0.4641)             |
+| 2.9815     | 49100     | 0.4635        | -                            |
+| 2.9876     | 49200     | 0.4235        | -                            |
+| 2.9937     | 49300     | 0.4913        | -                            |
+| 2.9998     | 49400     | 0.4842        | -                            |
+| -1         | -1        | -             | 0.7068 (+0.4669)             |
+
+* The bold row denotes the saved checkpoint.
+</details>
+
+### Framework Versions
+- Python: 3.11.12
+- Sentence Transformers: 4.1.0
+- Transformers: 4.51.3
+- PyTorch: 2.6.0+cu124
+- Accelerate: 1.6.0
+- Datasets: 3.6.0
+- Tokenizers: 0.21.1
+
+## Citation
+
+### BibTeX
+
+#### Sentence Transformers
+```bibtex
+@inproceedings{reimers-2019-sentence-bert,
+    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
+    author = "Reimers, Nils and Gurevych, Iryna",
+    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
+    month = "11",
+    year = "2019",
+    publisher = "Association for Computational Linguistics",
+    url = "https://arxiv.org/abs/1908.10084",
+}
+```
+
+<!--
+## Glossary
+
+*Clearly define terms in order to be accessible across audiences.*
+-->
+
+<!--
+## Model Card Authors
+
+*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
+-->
+
+<!--
+## Model Card Contact
+
+*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
+-->

final/config.json

@@ -0,0 +1,35 @@
+{
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
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