| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: distilbert-base-uncased_fold_5_binary_v1 |
| 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. --> |
|
|
| # distilbert-base-uncased_fold_5_binary_v1 |
|
|
| 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: 1.6980 |
| - F1: 0.8110 |
|
|
| ## 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: 25 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | No log | 1.0 | 288 | 0.4412 | 0.7981 | |
| | 0.396 | 2.0 | 576 | 0.4419 | 0.8078 | |
| | 0.396 | 3.0 | 864 | 0.4955 | 0.8166 | |
| | 0.2019 | 4.0 | 1152 | 0.6341 | 0.8075 | |
| | 0.2019 | 5.0 | 1440 | 1.0351 | 0.7979 | |
| | 0.0808 | 6.0 | 1728 | 1.1818 | 0.7844 | |
| | 0.0315 | 7.0 | 2016 | 1.2530 | 0.8051 | |
| | 0.0315 | 8.0 | 2304 | 1.3568 | 0.7937 | |
| | 0.0143 | 9.0 | 2592 | 1.4009 | 0.8045 | |
| | 0.0143 | 10.0 | 2880 | 1.5333 | 0.7941 | |
| | 0.0066 | 11.0 | 3168 | 1.5242 | 0.7982 | |
| | 0.0066 | 12.0 | 3456 | 1.5752 | 0.8050 | |
| | 0.0091 | 13.0 | 3744 | 1.5199 | 0.8046 | |
| | 0.0111 | 14.0 | 4032 | 1.5319 | 0.8117 | |
| | 0.0111 | 15.0 | 4320 | 1.5333 | 0.8156 | |
| | 0.0072 | 16.0 | 4608 | 1.5461 | 0.8192 | |
| | 0.0072 | 17.0 | 4896 | 1.5288 | 0.8252 | |
| | 0.0048 | 18.0 | 5184 | 1.5725 | 0.8078 | |
| | 0.0048 | 19.0 | 5472 | 1.5896 | 0.8138 | |
| | 0.0032 | 20.0 | 5760 | 1.6917 | 0.8071 | |
| | 0.0028 | 21.0 | 6048 | 1.6608 | 0.8109 | |
| | 0.0028 | 22.0 | 6336 | 1.7013 | 0.8122 | |
| | 0.0029 | 23.0 | 6624 | 1.6769 | 0.8148 | |
| | 0.0029 | 24.0 | 6912 | 1.6906 | 0.8100 | |
| | 0.0006 | 25.0 | 7200 | 1.6980 | 0.8110 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.21.0 |
| - Pytorch 1.12.0+cu113 |
| - Datasets 2.4.0 |
| - Tokenizers 0.12.1 |
|
|
