| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: distilbert-base-uncased_fold_4_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_4_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: 1.2977 |
| - F1: 0.8083 |
| |
| ## 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 | 0.3701 | 0.7903 | |
| | 0.4005 | 2.0 | 578 | 0.3669 | 0.7994 | |
| | 0.4005 | 3.0 | 867 | 0.5038 | 0.7955 | |
| | 0.1945 | 4.0 | 1156 | 0.6353 | 0.8006 | |
| | 0.1945 | 5.0 | 1445 | 0.8974 | 0.7826 | |
| | 0.0909 | 6.0 | 1734 | 0.8533 | 0.7764 | |
| | 0.0389 | 7.0 | 2023 | 0.9969 | 0.7957 | |
| | 0.0389 | 8.0 | 2312 | 1.0356 | 0.7952 | |
| | 0.0231 | 9.0 | 2601 | 1.1538 | 0.7963 | |
| | 0.0231 | 10.0 | 2890 | 1.2011 | 0.7968 | |
| | 0.0051 | 11.0 | 3179 | 1.2329 | 0.7935 | |
| | 0.0051 | 12.0 | 3468 | 1.2829 | 0.8056 | |
| | 0.0066 | 13.0 | 3757 | 1.2946 | 0.7956 | |
| | 0.004 | 14.0 | 4046 | 1.2977 | 0.8083 | |
| | 0.004 | 15.0 | 4335 | 1.3970 | 0.7957 | |
| | 0.0007 | 16.0 | 4624 | 1.3361 | 0.7917 | |
| | 0.0007 | 17.0 | 4913 | 1.5782 | 0.7954 | |
| | 0.0107 | 18.0 | 5202 | 1.4641 | 0.7900 | |
| | 0.0107 | 19.0 | 5491 | 1.4490 | 0.7957 | |
| | 0.0058 | 20.0 | 5780 | 1.4607 | 0.7932 | |
| | 0.0016 | 21.0 | 6069 | 1.5048 | 0.7939 | |
| | 0.0016 | 22.0 | 6358 | 1.5219 | 0.7945 | |
| | 0.0027 | 23.0 | 6647 | 1.4783 | 0.7937 | |
| | 0.0027 | 24.0 | 6936 | 1.4715 | 0.7981 | |
| | 0.0004 | 25.0 | 7225 | 1.4989 | 0.7900 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.21.0 |
| - Pytorch 1.12.0+cu113 |
| - Datasets 2.4.0 |
| - Tokenizers 0.12.1 |
| |
