| --- |
| library_name: transformers |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: CollectedDataModel |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # CollectedDataModel |
|
|
| This model was trained from scratch on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4365 |
|
|
| ## Model description |
|
|
| More information needed |
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|
| ## Intended uses & limitations |
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| More information needed |
|
|
| ## Training and evaluation data |
|
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| More information needed |
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|
| ## Training procedure |
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|
| ### Training hyperparameters |
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| The following hyperparameters were used during training: |
| - learning_rate: 0.0001 |
| - train_batch_size: 4 |
| - eval_batch_size: 2 |
| - seed: 42 |
| - gradient_accumulation_steps: 8 |
| - total_train_batch_size: 32 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 100 |
| - training_steps: 1000 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:------:|:----:|:---------------:| |
| | 0.4302 | 0.9913 | 100 | 0.4359 | |
| | 0.4275 | 1.9827 | 200 | 0.4396 | |
| | 0.4208 | 2.9740 | 300 | 0.4366 | |
| | 0.4217 | 3.9653 | 400 | 0.4389 | |
| | 0.4154 | 4.9566 | 500 | 0.4282 | |
| | 0.4173 | 5.9480 | 600 | 0.4362 | |
| | 0.4127 | 6.9393 | 700 | 0.4378 | |
| | 0.4104 | 7.9306 | 800 | 0.4340 | |
| | 0.4076 | 8.9219 | 900 | 0.4347 | |
| | 0.4065 | 9.9133 | 1000 | 0.4365 | |
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| ### Framework versions |
|
|
| - Transformers 4.44.2 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.0.1 |
| - Tokenizers 0.19.1 |
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|
