| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: distilbert-base-uncased_fold_3_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_3_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: 1.9405 |
| - F1: 0.7878 |
|
|
| ## 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 | 0.4630 | 0.7897 | |
| | 0.3954 | 2.0 | 578 | 0.4549 | 0.7936 | |
| | 0.3954 | 3.0 | 867 | 0.6527 | 0.7868 | |
| | 0.1991 | 4.0 | 1156 | 0.7510 | 0.7951 | |
| | 0.1991 | 5.0 | 1445 | 0.9327 | 0.8000 | |
| | 0.095 | 6.0 | 1734 | 1.0974 | 0.7859 | |
| | 0.0347 | 7.0 | 2023 | 1.2692 | 0.7919 | |
| | 0.0347 | 8.0 | 2312 | 1.3718 | 0.7921 | |
| | 0.0105 | 9.0 | 2601 | 1.4679 | 0.7999 | |
| | 0.0105 | 10.0 | 2890 | 1.5033 | 0.8070 | |
| | 0.0079 | 11.0 | 3179 | 1.6074 | 0.8008 | |
| | 0.0079 | 12.0 | 3468 | 1.6921 | 0.7904 | |
| | 0.0053 | 13.0 | 3757 | 1.7079 | 0.7945 | |
| | 0.0054 | 14.0 | 4046 | 1.8361 | 0.7887 | |
| | 0.0054 | 15.0 | 4335 | 1.7695 | 0.7873 | |
| | 0.0046 | 16.0 | 4624 | 1.7934 | 0.7917 | |
| | 0.0046 | 17.0 | 4913 | 1.8036 | 0.8008 | |
| | 0.0064 | 18.0 | 5202 | 1.8780 | 0.7888 | |
| | 0.0064 | 19.0 | 5491 | 1.8943 | 0.7923 | |
| | 0.0032 | 20.0 | 5780 | 1.8694 | 0.7905 | |
| | 0.002 | 21.0 | 6069 | 1.9348 | 0.7869 | |
| | 0.002 | 22.0 | 6358 | 1.9578 | 0.7804 | |
| | 0.0036 | 23.0 | 6647 | 1.9438 | 0.7827 | |
| | 0.0036 | 24.0 | 6936 | 1.9386 | 0.7878 | |
| | 0.0011 | 25.0 | 7225 | 1.9405 | 0.7878 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.21.0 |
| - Pytorch 1.12.0+cu113 |
| - Datasets 2.4.0 |
| - Tokenizers 0.12.1 |
|
|
