| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: distilbert-base-uncased_fold_5_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_5_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: 0.5093 |
| - F1: 0.7801 |
| |
| ## 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 | 0.4760 | 0.7315 | |
| | 0.3992 | 2.0 | 576 | 0.4428 | 0.7785 | |
| | 0.3992 | 3.0 | 864 | 0.5093 | 0.7801 | |
| | 0.2021 | 4.0 | 1152 | 0.6588 | 0.7634 | |
| | 0.2021 | 5.0 | 1440 | 0.9174 | 0.7713 | |
| | 0.0945 | 6.0 | 1728 | 0.9832 | 0.7726 | |
| | 0.0321 | 7.0 | 2016 | 1.2103 | 0.7672 | |
| | 0.0321 | 8.0 | 2304 | 1.3759 | 0.7616 | |
| | 0.0134 | 9.0 | 2592 | 1.4405 | 0.7570 | |
| | 0.0134 | 10.0 | 2880 | 1.4591 | 0.7710 | |
| | 0.0117 | 11.0 | 3168 | 1.4947 | 0.7713 | |
| | 0.0117 | 12.0 | 3456 | 1.6224 | 0.7419 | |
| | 0.0081 | 13.0 | 3744 | 1.6462 | 0.7520 | |
| | 0.0083 | 14.0 | 4032 | 1.6880 | 0.7637 | |
| | 0.0083 | 15.0 | 4320 | 1.7080 | 0.7380 | |
| | 0.0048 | 16.0 | 4608 | 1.7352 | 0.7551 | |
| | 0.0048 | 17.0 | 4896 | 1.6761 | 0.7713 | |
| | 0.0024 | 18.0 | 5184 | 1.7553 | 0.76 | |
| | 0.0024 | 19.0 | 5472 | 1.7312 | 0.7673 | |
| | 0.005 | 20.0 | 5760 | 1.7334 | 0.7713 | |
| | 0.0032 | 21.0 | 6048 | 1.7963 | 0.7578 | |
| | 0.0032 | 22.0 | 6336 | 1.7529 | 0.7679 | |
| | 0.0025 | 23.0 | 6624 | 1.7741 | 0.7662 | |
| | 0.0025 | 24.0 | 6912 | 1.7515 | 0.7679 | |
| | 0.0004 | 25.0 | 7200 | 1.7370 | 0.7765 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.21.0 |
| - Pytorch 1.12.0+cu113 |
| - Datasets 2.4.0 |
| - Tokenizers 0.12.1 |
| |
