| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| base_model: distilbert-base-uncased |
| model-index: |
| - name: SS_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. --> |
|
|
| # SS_model |
| |
| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3980 |
| - Accuracy: 0.9587 |
| |
| ## 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: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 20 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | 0.153 | 1.0 | 4301 | 0.1472 | 0.9526 | |
| | 0.1165 | 2.0 | 8602 | 0.1376 | 0.9562 | |
| | 0.0951 | 3.0 | 12903 | 0.1462 | 0.9596 | |
| | 0.0851 | 4.0 | 17204 | 0.1550 | 0.9602 | |
| | 0.0709 | 5.0 | 21505 | 0.1848 | 0.9596 | |
| | 0.069 | 6.0 | 25806 | 0.2027 | 0.9586 | |
| | 0.0591 | 7.0 | 30107 | 0.2266 | 0.9582 | |
| | 0.047 | 8.0 | 34408 | 0.2110 | 0.9573 | |
| | 0.0391 | 9.0 | 38709 | 0.2405 | 0.9577 | |
| | 0.0333 | 10.0 | 43010 | 0.2865 | 0.9566 | |
| | 0.0336 | 11.0 | 47311 | 0.2671 | 0.9588 | |
| | 0.0226 | 12.0 | 51612 | 0.2743 | 0.9567 | |
| | 0.0266 | 13.0 | 55913 | 0.3281 | 0.9577 | |
| | 0.0191 | 14.0 | 60214 | 0.3062 | 0.9572 | |
| | 0.0232 | 15.0 | 64515 | 0.3479 | 0.9585 | |
| | 0.0149 | 16.0 | 68816 | 0.3542 | 0.9587 | |
| | 0.0099 | 17.0 | 73117 | 0.3646 | 0.9587 | |
| | 0.0123 | 18.0 | 77418 | 0.3721 | 0.9584 | |
| | 0.0091 | 19.0 | 81719 | 0.3896 | 0.9590 | |
| | 0.0086 | 20.0 | 86020 | 0.3980 | 0.9587 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.28.0 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.14.4 |
| - Tokenizers 0.13.3 |
| |
