| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: distilbert-base-uncased_fold_3_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_3_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: 1.8310 |
| - F1: 0.7584 |
| |
| ## 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 | 289 | 0.4560 | 0.7522 | |
| | 0.4008 | 2.0 | 578 | 0.4790 | 0.7567 | |
| | 0.4008 | 3.0 | 867 | 0.6368 | 0.7557 | |
| | 0.1967 | 4.0 | 1156 | 0.6854 | 0.7534 | |
| | 0.1967 | 5.0 | 1445 | 0.9823 | 0.7309 | |
| | 0.0768 | 6.0 | 1734 | 1.2531 | 0.7511 | |
| | 0.0202 | 7.0 | 2023 | 1.2906 | 0.7391 | |
| | 0.0202 | 8.0 | 2312 | 1.4025 | 0.7460 | |
| | 0.0087 | 9.0 | 2601 | 1.5713 | 0.7507 | |
| | 0.0087 | 10.0 | 2890 | 1.4212 | 0.7528 | |
| | 0.0162 | 11.0 | 3179 | 1.5775 | 0.7511 | |
| | 0.0162 | 12.0 | 3468 | 1.6361 | 0.7377 | |
| | 0.0048 | 13.0 | 3757 | 1.6972 | 0.7542 | |
| | 0.0098 | 14.0 | 4046 | 1.6569 | 0.7565 | |
| | 0.0098 | 15.0 | 4335 | 1.7547 | 0.7325 | |
| | 0.0042 | 16.0 | 4624 | 1.8108 | 0.7544 | |
| | 0.0042 | 17.0 | 4913 | 1.7593 | 0.7554 | |
| | 0.0041 | 18.0 | 5202 | 1.7582 | 0.7551 | |
| | 0.0041 | 19.0 | 5491 | 1.8200 | 0.7512 | |
| | 0.0029 | 20.0 | 5780 | 1.8310 | 0.7584 | |
| | 0.0018 | 21.0 | 6069 | 1.8146 | 0.7568 | |
| | 0.0018 | 22.0 | 6358 | 1.7870 | 0.7558 | |
| | 0.0029 | 23.0 | 6647 | 1.8508 | 0.7530 | |
| | 0.0029 | 24.0 | 6936 | 1.8327 | 0.7543 | |
| | 0.0001 | 25.0 | 7225 | 1.8546 | 0.7561 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.21.0 |
| - Pytorch 1.12.0+cu113 |
| - Datasets 2.4.0 |
| - Tokenizers 0.12.1 |
| |
