| --- |
| license: mit |
| tags: |
| - generated_from_trainer |
| datasets: |
| - allocine |
| model-index: |
| - name: model |
| 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. --> |
|
|
| # model |
|
|
| This model is a fine-tuned version of [cmarkea/distilcamembert-base](https://huggingface.co/cmarkea/distilcamembert-base) on the allocine dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 2.0254 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 2e-05 |
| - train_batch_size: 64 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 20.0 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 2.4388 | 1.0 | 157 | 2.1637 | |
| | 2.288 | 2.0 | 314 | 2.1697 | |
| | 2.2444 | 3.0 | 471 | 2.1150 | |
| | 2.2166 | 4.0 | 628 | 2.0906 | |
| | 2.1754 | 5.0 | 785 | 2.0899 | |
| | 2.1604 | 6.0 | 942 | 2.0797 | |
| | 2.1299 | 7.0 | 1099 | 2.0589 | |
| | 2.1195 | 8.0 | 1256 | 2.0178 | |
| | 2.1258 | 9.0 | 1413 | 2.0348 | |
| | 2.1071 | 10.0 | 1570 | 2.0090 | |
| | 2.0888 | 11.0 | 1727 | 2.0047 | |
| | 2.0792 | 12.0 | 1884 | 2.0219 | |
| | 2.0687 | 13.0 | 2041 | 2.0080 | |
| | 2.0527 | 14.0 | 2198 | 2.0298 | |
| | 2.0589 | 15.0 | 2355 | 1.9869 | |
| | 2.0518 | 16.0 | 2512 | 2.0152 | |
| | 2.0409 | 17.0 | 2669 | 2.0247 | |
| | 2.0507 | 18.0 | 2826 | 1.9928 | |
| | 2.0366 | 19.0 | 2983 | 2.0175 | |
| | 2.0386 | 20.0 | 3140 | 1.9487 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.21.2 |
| - Pytorch 1.12.1+cu113 |
| - Datasets 2.4.0 |
| - Tokenizers 0.12.1 |
|
|
