| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: distilbert-base-uncased_fold_2_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_2_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: 1.8833 |
| - F1: 0.7841 |
|
|
| ## 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 | 0.4060 | 0.8070 | |
| | 0.3981 | 2.0 | 580 | 0.4534 | 0.8072 | |
| | 0.3981 | 3.0 | 870 | 0.5460 | 0.7961 | |
| | 0.1985 | 4.0 | 1160 | 0.8684 | 0.7818 | |
| | 0.1985 | 5.0 | 1450 | 0.9009 | 0.7873 | |
| | 0.0844 | 6.0 | 1740 | 1.1529 | 0.7825 | |
| | 0.0329 | 7.0 | 2030 | 1.3185 | 0.7850 | |
| | 0.0329 | 8.0 | 2320 | 1.4110 | 0.7862 | |
| | 0.0109 | 9.0 | 2610 | 1.4751 | 0.7784 | |
| | 0.0109 | 10.0 | 2900 | 1.6276 | 0.7723 | |
| | 0.0071 | 11.0 | 3190 | 1.6779 | 0.7861 | |
| | 0.0071 | 12.0 | 3480 | 1.6258 | 0.7850 | |
| | 0.0041 | 13.0 | 3770 | 1.6324 | 0.7903 | |
| | 0.0109 | 14.0 | 4060 | 1.7563 | 0.7932 | |
| | 0.0109 | 15.0 | 4350 | 1.6740 | 0.7906 | |
| | 0.0079 | 16.0 | 4640 | 1.7468 | 0.7944 | |
| | 0.0079 | 17.0 | 4930 | 1.7095 | 0.7879 | |
| | 0.0067 | 18.0 | 5220 | 1.7293 | 0.7912 | |
| | 0.0021 | 19.0 | 5510 | 1.7875 | 0.7848 | |
| | 0.0021 | 20.0 | 5800 | 1.7462 | 0.7906 | |
| | 0.0026 | 21.0 | 6090 | 1.8549 | 0.7815 | |
| | 0.0026 | 22.0 | 6380 | 1.8314 | 0.7860 | |
| | 0.0021 | 23.0 | 6670 | 1.8577 | 0.7839 | |
| | 0.0021 | 24.0 | 6960 | 1.8548 | 0.7883 | |
| | 0.0001 | 25.0 | 7250 | 1.8833 | 0.7841 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.21.0 |
| - Pytorch 1.12.0+cu113 |
| - Datasets 2.4.0 |
| - Tokenizers 0.12.1 |
|
|
