| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: distilbert-base-uncased_fold_9_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_9_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: 1.6965 |
| - F1: 0.8090 |
|
|
| ## 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 | 291 | 0.4193 | 0.7989 | |
| | 0.3993 | 2.0 | 582 | 0.4039 | 0.8026 | |
| | 0.3993 | 3.0 | 873 | 0.5227 | 0.7995 | |
| | 0.2044 | 4.0 | 1164 | 0.7264 | 0.8011 | |
| | 0.2044 | 5.0 | 1455 | 0.8497 | 0.8007 | |
| | 0.0882 | 6.0 | 1746 | 0.9543 | 0.8055 | |
| | 0.0374 | 7.0 | 2037 | 1.1349 | 0.7997 | |
| | 0.0374 | 8.0 | 2328 | 1.3175 | 0.8009 | |
| | 0.0151 | 9.0 | 2619 | 1.3585 | 0.8030 | |
| | 0.0151 | 10.0 | 2910 | 1.4202 | 0.8067 | |
| | 0.0068 | 11.0 | 3201 | 1.4364 | 0.8108 | |
| | 0.0068 | 12.0 | 3492 | 1.4443 | 0.8088 | |
| | 0.0096 | 13.0 | 3783 | 1.5308 | 0.8075 | |
| | 0.0031 | 14.0 | 4074 | 1.5061 | 0.8020 | |
| | 0.0031 | 15.0 | 4365 | 1.5769 | 0.7980 | |
| | 0.0048 | 16.0 | 4656 | 1.5962 | 0.8038 | |
| | 0.0048 | 17.0 | 4947 | 1.5383 | 0.8085 | |
| | 0.0067 | 18.0 | 5238 | 1.5456 | 0.8158 | |
| | 0.0062 | 19.0 | 5529 | 1.6325 | 0.8044 | |
| | 0.0062 | 20.0 | 5820 | 1.5430 | 0.8141 | |
| | 0.0029 | 21.0 | 6111 | 1.6590 | 0.8117 | |
| | 0.0029 | 22.0 | 6402 | 1.6650 | 0.8112 | |
| | 0.0017 | 23.0 | 6693 | 1.7016 | 0.8053 | |
| | 0.0017 | 24.0 | 6984 | 1.6998 | 0.8090 | |
| | 0.0011 | 25.0 | 7275 | 1.6965 | 0.8090 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.21.0 |
| - Pytorch 1.12.0+cu113 |
| - Datasets 2.4.0 |
| - Tokenizers 0.12.1 |
|
|
