| --- |
| license: apache-2.0 |
| base_model: google-bert/bert-base-cased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| - recall |
| model-index: |
| - name: bert-base-cased |
| 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-base-cased |
|
|
| This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6750 |
| - F1 Macro: 0.9031 |
| - F1: 0.9370 |
| - F1 Neg: 0.8692 |
| - Acc: 0.915 |
| - Prec: 0.9336 |
| - Recall: 0.9405 |
| - Mcc: 0.8063 |
|
|
| ## 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: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 5 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 | F1 Neg | Acc | Prec | Recall | Mcc | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|:------:|:------:| |
| | 0.1886 | 1.0 | 2125 | 0.3952 | 0.8938 | 0.9283 | 0.8593 | 0.905 | 0.9425 | 0.9145 | 0.7884 | |
| | 0.0578 | 2.0 | 4250 | 0.6750 | 0.9031 | 0.9370 | 0.8692 | 0.915 | 0.9336 | 0.9405 | 0.8063 | |
| | 0.0243 | 3.0 | 6375 | 0.7559 | 0.8922 | 0.9294 | 0.8550 | 0.905 | 0.9294 | 0.9294 | 0.7843 | |
| | 0.0084 | 4.0 | 8500 | 0.8553 | 0.9001 | 0.9353 | 0.8649 | 0.9125 | 0.9301 | 0.9405 | 0.8003 | |
| | 0.0131 | 5.0 | 10625 | 0.8916 | 0.8974 | 0.9333 | 0.8615 | 0.91 | 0.9299 | 0.9368 | 0.7949 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.38.2 |
| - Pytorch 2.2.1+cu121 |
| - Datasets 2.18.0 |
| - Tokenizers 0.15.2 |
|
|
