Text Classification
Transformers
PyTorch
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use DReAMy-lib/xlm-roberta-large-DreamBank-emotion-presence with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DReAMy-lib/xlm-roberta-large-DreamBank-emotion-presence with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DReAMy-lib/xlm-roberta-large-DreamBank-emotion-presence")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DReAMy-lib/xlm-roberta-large-DreamBank-emotion-presence") model = AutoModelForSequenceClassification.from_pretrained("DReAMy-lib/xlm-roberta-large-DreamBank-emotion-presence") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 2865a25
Update README.md
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README.md
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model-index:
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- name: xlm-roberta-large-DreamBank
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the None dataset.
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It achieves the following results on the evaluation set:
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- F1: 0.8621
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- Roc Auc: 0.9069
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- Accuracy: 0.6973
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## Model description
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- Transformers 4.25.1
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- Pytorch 1.12.1
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- Datasets 2.5.1
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- Tokenizers 0.12.1
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model-index:
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- name: xlm-roberta-large-DreamBank
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results: []
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widget:
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- text: >-
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I dreamed that Hannah and Sue and I travelled back in time to meet her
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parents. Weird.
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pipeline_tag: text-classification
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the None dataset.
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It achieves the following results on the evaluation set:
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Best result (loaded model)
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- F1: 0.8621
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## Model description
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- Transformers 4.25.1
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- Pytorch 1.12.1
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- Datasets 2.5.1
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- Tokenizers 0.12.1
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