Instructions to use alexgrigoras/sdg_chronos_t5_small_dunnhumby with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alexgrigoras/sdg_chronos_t5_small_dunnhumby with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("alexgrigoras/sdg_chronos_t5_small_dunnhumby", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload SDG checkpoint
Browse files- adapter_config.json +5 -5
- adapter_model.safetensors +1 -1
- checkpoint-100/README.md +206 -0
- checkpoint-100/adapter_config.json +45 -0
- checkpoint-100/adapter_model.safetensors +3 -0
- checkpoint-100/optimizer.pt +3 -0
- checkpoint-100/rng_state.pth +3 -0
- checkpoint-100/scheduler.pt +3 -0
- checkpoint-100/tokenizer.json +0 -0
- checkpoint-100/tokenizer_config.json +112 -0
- checkpoint-100/trainer_state.json +94 -0
- checkpoint-100/training_args.bin +3 -0
- checkpoint-300/README.md +206 -0
- checkpoint-300/adapter_config.json +45 -0
- checkpoint-300/adapter_model.safetensors +3 -0
- checkpoint-300/optimizer.pt +3 -0
- checkpoint-300/rng_state.pth +3 -0
- checkpoint-300/scheduler.pt +3 -0
- checkpoint-300/tokenizer.json +0 -0
- checkpoint-300/tokenizer_config.json +112 -0
- checkpoint-300/trainer_state.json +214 -0
- checkpoint-300/training_args.bin +3 -0
- privacy_reference_bank.npy +3 -0
- privacy_reference_stats.json +6 -0
- sdg_config.json +15 -5
- training_info.json +13 -4
adapter_config.json
CHANGED
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"loftq_config": {},
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"lora_alpha": 64,
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"lora_bias": false,
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-
"lora_dropout": 0.
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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],
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"target_parameters": null,
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"task_type": "SEQ_2_SEQ_LM",
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"loftq_config": {},
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"lora_alpha": 64,
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"lora_bias": false,
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"lora_dropout": 0.1,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"target_parameters": null,
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"task_type": "SEQ_2_SEQ_LM",
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 34675328
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version https://git-lfs.github.com/spec/v1
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oid sha256:d132234d93d10ab49e2abad26ef3a2438eda16c5c8f3a3be863b34dcda89f16f
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size 34675328
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checkpoint-100/README.md
ADDED
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+
---
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| 2 |
+
base_model: amazon/chronos-t5-small
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library_name: peft
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tags:
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- base_model:adapter:amazon/chronos-t5-small
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- lora
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- transformers
|
| 8 |
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---
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| 9 |
+
|
| 10 |
+
# Model Card for Model ID
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| 11 |
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<!-- Provide a quick summary of what the model is/does. -->
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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| 22 |
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| 23 |
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- **Developed by:** [More Information Needed]
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| 25 |
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- **Funded by [optional]:** [More Information Needed]
|
| 26 |
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- **Shared by [optional]:** [More Information Needed]
|
| 27 |
+
- **Model type:** [More Information Needed]
|
| 28 |
+
- **Language(s) (NLP):** [More Information Needed]
|
| 29 |
+
- **License:** [More Information Needed]
|
| 30 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
| 31 |
+
|
| 32 |
+
### Model Sources [optional]
|
| 33 |
+
|
| 34 |
+
<!-- Provide the basic links for the model. -->
|
| 35 |
+
|
| 36 |
+
- **Repository:** [More Information Needed]
|
| 37 |
+
- **Paper [optional]:** [More Information Needed]
|
| 38 |
+
- **Demo [optional]:** [More Information Needed]
|
| 39 |
+
|
| 40 |
+
## Uses
|
| 41 |
+
|
| 42 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
| 43 |
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|
| 44 |
+
### Direct Use
|
| 45 |
+
|
| 46 |
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 47 |
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|
| 48 |
+
[More Information Needed]
|
| 49 |
+
|
| 50 |
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### Downstream Use [optional]
|
| 51 |
+
|
| 52 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
| 53 |
+
|
| 54 |
+
[More Information Needed]
|
| 55 |
+
|
| 56 |
+
### Out-of-Scope Use
|
| 57 |
+
|
| 58 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
| 59 |
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|
| 60 |
+
[More Information Needed]
|
| 61 |
+
|
| 62 |
+
## Bias, Risks, and Limitations
|
| 63 |
+
|
| 64 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
| 65 |
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|
| 66 |
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[More Information Needed]
|
| 67 |
+
|
| 68 |
+
### Recommendations
|
| 69 |
+
|
| 70 |
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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| 71 |
+
|
| 72 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
| 73 |
+
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| 74 |
+
## How to Get Started with the Model
|
| 75 |
+
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| 76 |
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Use the code below to get started with the model.
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| 77 |
+
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| 78 |
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[More Information Needed]
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| 79 |
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| 80 |
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## Training Details
|
| 81 |
+
|
| 82 |
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### Training Data
|
| 83 |
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| 84 |
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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| 85 |
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[More Information Needed]
|
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|
| 88 |
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### Training Procedure
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| 89 |
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| 90 |
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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| 91 |
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#### Preprocessing [optional]
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| 93 |
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| 94 |
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[More Information Needed]
|
| 95 |
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|
| 96 |
+
|
| 97 |
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#### Training Hyperparameters
|
| 98 |
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|
| 99 |
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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| 100 |
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| 101 |
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#### Speeds, Sizes, Times [optional]
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| 102 |
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| 103 |
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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| 104 |
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[More Information Needed]
|
| 106 |
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| 107 |
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## Evaluation
|
| 108 |
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<!-- This section describes the evaluation protocols and provides the results. -->
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| 110 |
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### Testing Data, Factors & Metrics
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| 112 |
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| 113 |
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#### Testing Data
|
| 114 |
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|
| 115 |
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<!-- This should link to a Dataset Card if possible. -->
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| 116 |
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| 117 |
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[More Information Needed]
|
| 118 |
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|
| 119 |
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#### Factors
|
| 120 |
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| 121 |
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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| 122 |
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[More Information Needed]
|
| 124 |
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|
| 125 |
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#### Metrics
|
| 126 |
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| 127 |
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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| 129 |
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[More Information Needed]
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| 130 |
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### Results
|
| 132 |
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| 133 |
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[More Information Needed]
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| 134 |
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#### Summary
|
| 136 |
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| 138 |
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## Model Examination [optional]
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| 140 |
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| 141 |
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<!-- Relevant interpretability work for the model goes here -->
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| 142 |
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| 143 |
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[More Information Needed]
|
| 144 |
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|
| 145 |
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## Environmental Impact
|
| 146 |
+
|
| 147 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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| 148 |
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| 149 |
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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| 150 |
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| 151 |
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- **Hardware Type:** [More Information Needed]
|
| 152 |
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- **Hours used:** [More Information Needed]
|
| 153 |
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- **Cloud Provider:** [More Information Needed]
|
| 154 |
+
- **Compute Region:** [More Information Needed]
|
| 155 |
+
- **Carbon Emitted:** [More Information Needed]
|
| 156 |
+
|
| 157 |
+
## Technical Specifications [optional]
|
| 158 |
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| 159 |
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### Model Architecture and Objective
|
| 160 |
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|
| 161 |
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[More Information Needed]
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| 162 |
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| 163 |
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### Compute Infrastructure
|
| 164 |
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|
| 165 |
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[More Information Needed]
|
| 166 |
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| 167 |
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#### Hardware
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| 168 |
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| 169 |
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[More Information Needed]
|
| 170 |
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#### Software
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| 172 |
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[More Information Needed]
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| 174 |
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## Citation [optional]
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| 176 |
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| 177 |
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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| 178 |
+
|
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**BibTeX:**
|
| 180 |
+
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[More Information Needed]
|
| 182 |
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| 183 |
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**APA:**
|
| 184 |
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|
| 185 |
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[More Information Needed]
|
| 186 |
+
|
| 187 |
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## Glossary [optional]
|
| 188 |
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|
| 189 |
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
| 190 |
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|
| 191 |
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[More Information Needed]
|
| 192 |
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| 193 |
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## More Information [optional]
|
| 194 |
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| 195 |
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[More Information Needed]
|
| 196 |
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| 197 |
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## Model Card Authors [optional]
|
| 198 |
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| 199 |
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[More Information Needed]
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| 200 |
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## Model Card Contact
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| 202 |
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|
| 203 |
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[More Information Needed]
|
| 204 |
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### Framework versions
|
| 205 |
+
|
| 206 |
+
- PEFT 0.18.1
|
checkpoint-100/adapter_config.json
ADDED
|
@@ -0,0 +1,45 @@
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{
|
| 2 |
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"alora_invocation_tokens": null,
|
| 3 |
+
"alpha_pattern": {},
|
| 4 |
+
"arrow_config": null,
|
| 5 |
+
"auto_mapping": null,
|
| 6 |
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"base_model_name_or_path": "amazon/chronos-t5-small",
|
| 7 |
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"bias": "none",
|
| 8 |
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"corda_config": null,
|
| 9 |
+
"ensure_weight_tying": false,
|
| 10 |
+
"eva_config": null,
|
| 11 |
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"exclude_modules": null,
|
| 12 |
+
"fan_in_fan_out": false,
|
| 13 |
+
"inference_mode": true,
|
| 14 |
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"init_lora_weights": true,
|
| 15 |
+
"layer_replication": null,
|
| 16 |
+
"layers_pattern": null,
|
| 17 |
+
"layers_to_transform": null,
|
| 18 |
+
"loftq_config": {},
|
| 19 |
+
"lora_alpha": 32,
|
| 20 |
+
"lora_bias": false,
|
| 21 |
+
"lora_dropout": 0.1,
|
| 22 |
+
"megatron_config": null,
|
| 23 |
+
"megatron_core": "megatron.core",
|
| 24 |
+
"modules_to_save": null,
|
| 25 |
+
"peft_type": "LORA",
|
| 26 |
+
"peft_version": "0.18.1",
|
| 27 |
+
"qalora_group_size": 16,
|
| 28 |
+
"r": 16,
|
| 29 |
+
"rank_pattern": {},
|
| 30 |
+
"revision": null,
|
| 31 |
+
"target_modules": [
|
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|
| 1 |
+
---
|
| 2 |
+
base_model: amazon/chronos-t5-small
|
| 3 |
+
library_name: peft
|
| 4 |
+
tags:
|
| 5 |
+
- base_model:adapter:amazon/chronos-t5-small
|
| 6 |
+
- lora
|
| 7 |
+
- transformers
|
| 8 |
+
---
|
| 9 |
+
|
| 10 |
+
# Model Card for Model ID
|
| 11 |
+
|
| 12 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 13 |
+
|
| 14 |
+
|
| 15 |
+
|
| 16 |
+
## Model Details
|
| 17 |
+
|
| 18 |
+
### Model Description
|
| 19 |
+
|
| 20 |
+
<!-- Provide a longer summary of what this model is. -->
|
| 21 |
+
|
| 22 |
+
|
| 23 |
+
|
| 24 |
+
- **Developed by:** [More Information Needed]
|
| 25 |
+
- **Funded by [optional]:** [More Information Needed]
|
| 26 |
+
- **Shared by [optional]:** [More Information Needed]
|
| 27 |
+
- **Model type:** [More Information Needed]
|
| 28 |
+
- **Language(s) (NLP):** [More Information Needed]
|
| 29 |
+
- **License:** [More Information Needed]
|
| 30 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
| 31 |
+
|
| 32 |
+
### Model Sources [optional]
|
| 33 |
+
|
| 34 |
+
<!-- Provide the basic links for the model. -->
|
| 35 |
+
|
| 36 |
+
- **Repository:** [More Information Needed]
|
| 37 |
+
- **Paper [optional]:** [More Information Needed]
|
| 38 |
+
- **Demo [optional]:** [More Information Needed]
|
| 39 |
+
|
| 40 |
+
## Uses
|
| 41 |
+
|
| 42 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
| 43 |
+
|
| 44 |
+
### Direct Use
|
| 45 |
+
|
| 46 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 47 |
+
|
| 48 |
+
[More Information Needed]
|
| 49 |
+
|
| 50 |
+
### Downstream Use [optional]
|
| 51 |
+
|
| 52 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
| 53 |
+
|
| 54 |
+
[More Information Needed]
|
| 55 |
+
|
| 56 |
+
### Out-of-Scope Use
|
| 57 |
+
|
| 58 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
| 59 |
+
|
| 60 |
+
[More Information Needed]
|
| 61 |
+
|
| 62 |
+
## Bias, Risks, and Limitations
|
| 63 |
+
|
| 64 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
| 65 |
+
|
| 66 |
+
[More Information Needed]
|
| 67 |
+
|
| 68 |
+
### Recommendations
|
| 69 |
+
|
| 70 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
| 71 |
+
|
| 72 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
| 73 |
+
|
| 74 |
+
## How to Get Started with the Model
|
| 75 |
+
|
| 76 |
+
Use the code below to get started with the model.
|
| 77 |
+
|
| 78 |
+
[More Information Needed]
|
| 79 |
+
|
| 80 |
+
## Training Details
|
| 81 |
+
|
| 82 |
+
### Training Data
|
| 83 |
+
|
| 84 |
+
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
| 85 |
+
|
| 86 |
+
[More Information Needed]
|
| 87 |
+
|
| 88 |
+
### Training Procedure
|
| 89 |
+
|
| 90 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
| 91 |
+
|
| 92 |
+
#### Preprocessing [optional]
|
| 93 |
+
|
| 94 |
+
[More Information Needed]
|
| 95 |
+
|
| 96 |
+
|
| 97 |
+
#### Training Hyperparameters
|
| 98 |
+
|
| 99 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
| 100 |
+
|
| 101 |
+
#### Speeds, Sizes, Times [optional]
|
| 102 |
+
|
| 103 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
| 104 |
+
|
| 105 |
+
[More Information Needed]
|
| 106 |
+
|
| 107 |
+
## Evaluation
|
| 108 |
+
|
| 109 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
| 110 |
+
|
| 111 |
+
### Testing Data, Factors & Metrics
|
| 112 |
+
|
| 113 |
+
#### Testing Data
|
| 114 |
+
|
| 115 |
+
<!-- This should link to a Dataset Card if possible. -->
|
| 116 |
+
|
| 117 |
+
[More Information Needed]
|
| 118 |
+
|
| 119 |
+
#### Factors
|
| 120 |
+
|
| 121 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
| 122 |
+
|
| 123 |
+
[More Information Needed]
|
| 124 |
+
|
| 125 |
+
#### Metrics
|
| 126 |
+
|
| 127 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
| 128 |
+
|
| 129 |
+
[More Information Needed]
|
| 130 |
+
|
| 131 |
+
### Results
|
| 132 |
+
|
| 133 |
+
[More Information Needed]
|
| 134 |
+
|
| 135 |
+
#### Summary
|
| 136 |
+
|
| 137 |
+
|
| 138 |
+
|
| 139 |
+
## Model Examination [optional]
|
| 140 |
+
|
| 141 |
+
<!-- Relevant interpretability work for the model goes here -->
|
| 142 |
+
|
| 143 |
+
[More Information Needed]
|
| 144 |
+
|
| 145 |
+
## Environmental Impact
|
| 146 |
+
|
| 147 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
| 148 |
+
|
| 149 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
| 150 |
+
|
| 151 |
+
- **Hardware Type:** [More Information Needed]
|
| 152 |
+
- **Hours used:** [More Information Needed]
|
| 153 |
+
- **Cloud Provider:** [More Information Needed]
|
| 154 |
+
- **Compute Region:** [More Information Needed]
|
| 155 |
+
- **Carbon Emitted:** [More Information Needed]
|
| 156 |
+
|
| 157 |
+
## Technical Specifications [optional]
|
| 158 |
+
|
| 159 |
+
### Model Architecture and Objective
|
| 160 |
+
|
| 161 |
+
[More Information Needed]
|
| 162 |
+
|
| 163 |
+
### Compute Infrastructure
|
| 164 |
+
|
| 165 |
+
[More Information Needed]
|
| 166 |
+
|
| 167 |
+
#### Hardware
|
| 168 |
+
|
| 169 |
+
[More Information Needed]
|
| 170 |
+
|
| 171 |
+
#### Software
|
| 172 |
+
|
| 173 |
+
[More Information Needed]
|
| 174 |
+
|
| 175 |
+
## Citation [optional]
|
| 176 |
+
|
| 177 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
| 178 |
+
|
| 179 |
+
**BibTeX:**
|
| 180 |
+
|
| 181 |
+
[More Information Needed]
|
| 182 |
+
|
| 183 |
+
**APA:**
|
| 184 |
+
|
| 185 |
+
[More Information Needed]
|
| 186 |
+
|
| 187 |
+
## Glossary [optional]
|
| 188 |
+
|
| 189 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
| 190 |
+
|
| 191 |
+
[More Information Needed]
|
| 192 |
+
|
| 193 |
+
## More Information [optional]
|
| 194 |
+
|
| 195 |
+
[More Information Needed]
|
| 196 |
+
|
| 197 |
+
## Model Card Authors [optional]
|
| 198 |
+
|
| 199 |
+
[More Information Needed]
|
| 200 |
+
|
| 201 |
+
## Model Card Contact
|
| 202 |
+
|
| 203 |
+
[More Information Needed]
|
| 204 |
+
### Framework versions
|
| 205 |
+
|
| 206 |
+
- PEFT 0.18.1
|
checkpoint-300/adapter_config.json
ADDED
|
@@ -0,0 +1,45 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"alora_invocation_tokens": null,
|
| 3 |
+
"alpha_pattern": {},
|
| 4 |
+
"arrow_config": null,
|
| 5 |
+
"auto_mapping": null,
|
| 6 |
+
"base_model_name_or_path": "amazon/chronos-t5-small",
|
| 7 |
+
"bias": "none",
|
| 8 |
+
"corda_config": null,
|
| 9 |
+
"ensure_weight_tying": false,
|
| 10 |
+
"eva_config": null,
|
| 11 |
+
"exclude_modules": null,
|
| 12 |
+
"fan_in_fan_out": false,
|
| 13 |
+
"inference_mode": true,
|
| 14 |
+
"init_lora_weights": true,
|
| 15 |
+
"layer_replication": null,
|
| 16 |
+
"layers_pattern": null,
|
| 17 |
+
"layers_to_transform": null,
|
| 18 |
+
"loftq_config": {},
|
| 19 |
+
"lora_alpha": 64,
|
| 20 |
+
"lora_bias": false,
|
| 21 |
+
"lora_dropout": 0.1,
|
| 22 |
+
"megatron_config": null,
|
| 23 |
+
"megatron_core": "megatron.core",
|
| 24 |
+
"modules_to_save": null,
|
| 25 |
+
"peft_type": "LORA",
|
| 26 |
+
"peft_version": "0.18.1",
|
| 27 |
+
"qalora_group_size": 16,
|
| 28 |
+
"r": 32,
|
| 29 |
+
"rank_pattern": {},
|
| 30 |
+
"revision": null,
|
| 31 |
+
"target_modules": [
|
| 32 |
+
"q",
|
| 33 |
+
"k",
|
| 34 |
+
"wi",
|
| 35 |
+
"wo",
|
| 36 |
+
"o",
|
| 37 |
+
"v"
|
| 38 |
+
],
|
| 39 |
+
"target_parameters": null,
|
| 40 |
+
"task_type": "SEQ_2_SEQ_LM",
|
| 41 |
+
"trainable_token_indices": null,
|
| 42 |
+
"use_dora": false,
|
| 43 |
+
"use_qalora": false,
|
| 44 |
+
"use_rslora": false
|
| 45 |
+
}
|
checkpoint-300/adapter_model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d132234d93d10ab49e2abad26ef3a2438eda16c5c8f3a3be863b34dcda89f16f
|
| 3 |
+
size 34675328
|
checkpoint-300/optimizer.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:5049a8d2f4f806a56d89530c4da05f252f9e18c9c0c9d0f2c59d1a2d5a51301d
|
| 3 |
+
size 34759371
|
checkpoint-300/rng_state.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:08f8fe56a72edfbc414d4b2de40ca33521959ba7ae7f211e3b88c911b03de69c
|
| 3 |
+
size 14391
|
checkpoint-300/scheduler.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:09c6773821ea9d3bef830d1d03869581ad60560d632621bbb6430b6bc17d445f
|
| 3 |
+
size 1465
|
checkpoint-300/tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
checkpoint-300/tokenizer_config.json
ADDED
|
@@ -0,0 +1,112 @@
|
|
|
|
|
|
|
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|
|
|
|
|
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|
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|
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|
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|
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|
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|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
|
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|
| 1 |
+
{
|
| 2 |
+
"backend": "tokenizers",
|
| 3 |
+
"eos_token": "</s>",
|
| 4 |
+
"extra_ids": 100,
|
| 5 |
+
"extra_special_tokens": [
|
| 6 |
+
"<extra_id_0>",
|
| 7 |
+
"<extra_id_1>",
|
| 8 |
+
"<extra_id_2>",
|
| 9 |
+
"<extra_id_3>",
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"step": 300
|
| 183 |
+
},
|
| 184 |
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{
|
| 185 |
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"epoch": 0.04181840358244324,
|
| 186 |
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|
| 187 |
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|
| 188 |
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|
| 189 |
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|
| 190 |
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"step": 300
|
| 191 |
+
}
|
| 192 |
+
],
|
| 193 |
+
"logging_steps": 25,
|
| 194 |
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"max_steps": 300,
|
| 195 |
+
"num_input_tokens_seen": 0,
|
| 196 |
+
"num_train_epochs": 1,
|
| 197 |
+
"save_steps": 300,
|
| 198 |
+
"stateful_callbacks": {
|
| 199 |
+
"TrainerControl": {
|
| 200 |
+
"args": {
|
| 201 |
+
"should_epoch_stop": false,
|
| 202 |
+
"should_evaluate": false,
|
| 203 |
+
"should_log": false,
|
| 204 |
+
"should_save": true,
|
| 205 |
+
"should_training_stop": true
|
| 206 |
+
},
|
| 207 |
+
"attributes": {}
|
| 208 |
+
}
|
| 209 |
+
},
|
| 210 |
+
"total_flos": 229911035904000.0,
|
| 211 |
+
"train_batch_size": 2,
|
| 212 |
+
"trial_name": null,
|
| 213 |
+
"trial_params": null
|
| 214 |
+
}
|
checkpoint-300/training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
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|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:6e3cbde0e32fb05322d5f55e6154336171a3e6994fa4c5c61e7e2ad0be268c10
|
| 3 |
+
size 5457
|
privacy_reference_bank.npy
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:27b2a98c927eb38de4afe90ee0cf075290b30bf898e7ce8935a526d7f4a002f5
|
| 3 |
+
size 240128
|
privacy_reference_stats.json
ADDED
|
@@ -0,0 +1,6 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"n_reference_windows": 2000,
|
| 3 |
+
"min_distance_threshold": 8.543635129928589,
|
| 4 |
+
"avg_real_nn_distance": 1678.3014648655792,
|
| 5 |
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"distance_quantile": 0.25
|
| 6 |
+
}
|
sdg_config.json
CHANGED
|
@@ -9,7 +9,7 @@
|
|
| 9 |
5.0
|
| 10 |
],
|
| 11 |
"learning_rate": 2.5e-05,
|
| 12 |
-
"train_steps":
|
| 13 |
"lora_rank": 32,
|
| 14 |
"lora_alpha": 64,
|
| 15 |
"batch_size": 2,
|
|
@@ -18,13 +18,23 @@
|
|
| 18 |
"max_target_length": 256,
|
| 19 |
"random_state": 42,
|
| 20 |
"task_prefix": "generate synthetic retail demand future from historical context",
|
| 21 |
-
"seasonality_strength": 0.
|
| 22 |
"seasonal_period": 7,
|
| 23 |
-
"seasonal_fallback_strength": 0.
|
| 24 |
"zero_threshold_for_sparsity": 0.6,
|
| 25 |
-
"prefer_backend": "
|
| 26 |
"use_special_tokens": true,
|
| 27 |
"add_calendar_features": true,
|
| 28 |
"warmup_ratio": 0.05,
|
| 29 |
-
"weight_decay": 0.01
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 30 |
}
|
|
|
|
| 9 |
5.0
|
| 10 |
],
|
| 11 |
"learning_rate": 2.5e-05,
|
| 12 |
+
"train_steps": 300,
|
| 13 |
"lora_rank": 32,
|
| 14 |
"lora_alpha": 64,
|
| 15 |
"batch_size": 2,
|
|
|
|
| 18 |
"max_target_length": 256,
|
| 19 |
"random_state": 42,
|
| 20 |
"task_prefix": "generate synthetic retail demand future from historical context",
|
| 21 |
+
"seasonality_strength": 0.6,
|
| 22 |
"seasonal_period": 7,
|
| 23 |
+
"seasonal_fallback_strength": 0.25,
|
| 24 |
"zero_threshold_for_sparsity": 0.6,
|
| 25 |
+
"prefer_backend": "lora",
|
| 26 |
"use_special_tokens": true,
|
| 27 |
"add_calendar_features": true,
|
| 28 |
"warmup_ratio": 0.05,
|
| 29 |
+
"weight_decay": 0.01,
|
| 30 |
+
"privacy_reference_max_windows": 2000,
|
| 31 |
+
"privacy_min_distance_quantile": 0.25,
|
| 32 |
+
"privacy_distance_penalty": 4.0,
|
| 33 |
+
"privacy_noise_strength": 0.1,
|
| 34 |
+
"privacy_baseline_blend": 0.25,
|
| 35 |
+
"privacy_training_jitter_prob": 0.6,
|
| 36 |
+
"privacy_training_jitter_strength": 0.1,
|
| 37 |
+
"privacy_deduplicate_examples": true,
|
| 38 |
+
"privacy_filter_enabled": true,
|
| 39 |
+
"privacy_filter_max_retries": 6
|
| 40 |
}
|
training_info.json
CHANGED
|
@@ -1,11 +1,20 @@
|
|
| 1 |
{
|
| 2 |
"train_examples": 114782,
|
| 3 |
"eval_examples": 12754,
|
| 4 |
-
"train_steps":
|
| 5 |
"learning_rate": 2.5e-05,
|
| 6 |
-
"train_runtime":
|
| 7 |
-
"train_loss":
|
| 8 |
"is_peft_model": true,
|
| 9 |
"backend_name": "lora",
|
| 10 |
-
"added_special_tokens": 4131
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 11 |
}
|
|
|
|
| 1 |
{
|
| 2 |
"train_examples": 114782,
|
| 3 |
"eval_examples": 12754,
|
| 4 |
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"train_steps": 300,
|
| 5 |
"learning_rate": 2.5e-05,
|
| 6 |
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"train_runtime": 1945.4336,
|
| 7 |
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"train_loss": 47.86641886393229,
|
| 8 |
"is_peft_model": true,
|
| 9 |
"backend_name": "lora",
|
| 10 |
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"added_special_tokens": 4131,
|
| 11 |
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"privacy_reference_windows": 2000,
|
| 12 |
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"privacy_deduplicated_examples": 0,
|
| 13 |
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"privacy_jittered_examples": 68730,
|
| 14 |
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"privacy_reference_stats": {
|
| 15 |
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"n_reference_windows": 2000,
|
| 16 |
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"min_distance_threshold": 8.543635129928589,
|
| 17 |
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"avg_real_nn_distance": 1678.3014648655792,
|
| 18 |
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"distance_quantile": 0.25
|
| 19 |
+
}
|
| 20 |
}
|