| --- |
| license: apache-2.0 |
| base_model: bert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: BERT_without_preprocessing_grid_search |
| 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. --> |
|
|
| # BERT_without_preprocessing_grid_search |
|
|
| This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6213 |
| - Precision: 0.8399 |
| - Recall: 0.8622 |
| - F1: 0.8498 |
| - Accuracy: 0.8798 |
|
|
| ## 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: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | No log | 1.0 | 257 | 0.6305 | 0.7254 | 0.8018 | 0.7512 | 0.8180 | |
| | 0.8689 | 2.0 | 514 | 0.4877 | 0.8120 | 0.8500 | 0.8245 | 0.8667 | |
| | 0.8689 | 3.0 | 771 | 0.4490 | 0.7911 | 0.8590 | 0.8148 | 0.8599 | |
| | 0.2702 | 4.0 | 1028 | 0.4748 | 0.8291 | 0.8689 | 0.8457 | 0.8730 | |
| | 0.2702 | 5.0 | 1285 | 0.5217 | 0.8326 | 0.8543 | 0.8413 | 0.8783 | |
| | 0.1505 | 6.0 | 1542 | 0.5288 | 0.8351 | 0.8650 | 0.8481 | 0.8754 | |
| | 0.1505 | 7.0 | 1799 | 0.5801 | 0.8417 | 0.8585 | 0.8487 | 0.8769 | |
| | 0.092 | 8.0 | 2056 | 0.5721 | 0.8402 | 0.8694 | 0.8535 | 0.8818 | |
| | 0.092 | 9.0 | 2313 | 0.6135 | 0.8453 | 0.8618 | 0.8522 | 0.8808 | |
| | 0.0723 | 10.0 | 2570 | 0.6213 | 0.8399 | 0.8622 | 0.8498 | 0.8798 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.31.0 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.14.4 |
| - Tokenizers 0.13.3 |
|
|
