| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: distilbert-base-uncased_fold_2_binary |
| 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_2_binary |
| |
| 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: 0.4724 |
| - F1: 0.7604 |
| |
| ## 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 | 290 | 0.4280 | 0.7515 | |
| | 0.4018 | 2.0 | 580 | 0.4724 | 0.7604 | |
| | 0.4018 | 3.0 | 870 | 0.5336 | 0.7428 | |
| | 0.1995 | 4.0 | 1160 | 0.8367 | 0.7476 | |
| | 0.1995 | 5.0 | 1450 | 0.9242 | 0.7412 | |
| | 0.089 | 6.0 | 1740 | 1.0987 | 0.7410 | |
| | 0.0318 | 7.0 | 2030 | 1.1853 | 0.7584 | |
| | 0.0318 | 8.0 | 2320 | 1.2509 | 0.7500 | |
| | 0.0189 | 9.0 | 2610 | 1.5060 | 0.7258 | |
| | 0.0189 | 10.0 | 2900 | 1.5607 | 0.7534 | |
| | 0.0084 | 11.0 | 3190 | 1.5871 | 0.7476 | |
| | 0.0084 | 12.0 | 3480 | 1.7206 | 0.7338 | |
| | 0.0047 | 13.0 | 3770 | 1.6776 | 0.7340 | |
| | 0.0068 | 14.0 | 4060 | 1.7339 | 0.7546 | |
| | 0.0068 | 15.0 | 4350 | 1.8279 | 0.7504 | |
| | 0.0025 | 16.0 | 4640 | 1.7791 | 0.7411 | |
| | 0.0025 | 17.0 | 4930 | 1.7917 | 0.7444 | |
| | 0.003 | 18.0 | 5220 | 1.7781 | 0.7559 | |
| | 0.0029 | 19.0 | 5510 | 1.8153 | 0.7559 | |
| | 0.0029 | 20.0 | 5800 | 1.7757 | 0.7414 | |
| | 0.0055 | 21.0 | 6090 | 1.8635 | 0.7454 | |
| | 0.0055 | 22.0 | 6380 | 1.8483 | 0.7460 | |
| | 0.001 | 23.0 | 6670 | 1.8620 | 0.7492 | |
| | 0.001 | 24.0 | 6960 | 1.9058 | 0.7508 | |
| | 0.0006 | 25.0 | 7250 | 1.8640 | 0.7504 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.21.0 |
| - Pytorch 1.12.0+cu113 |
| - Datasets 2.4.0 |
| - Tokenizers 0.12.1 |
| |
