| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: bertBasev2 |
| 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. --> |
|
|
| # bertBasev2 |
|
|
| This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0328 |
| - Precision: 0.9539 |
| - Recall: 0.9707 |
| - F1: 0.9622 |
| - Accuracy: 0.9911 |
|
|
| ## 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: 5e-05 |
| - train_batch_size: 1 |
| - eval_batch_size: 1 |
| - seed: 42 |
| - gradient_accumulation_steps: 8 |
| - total_train_batch_size: 8 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 7 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | 1.2004 | 1.0 | 1012 | 0.9504 | 0.2620 | 0.3519 | 0.3004 | 0.6856 | |
| | 1.0265 | 2.0 | 2024 | 0.6205 | 0.4356 | 0.5161 | 0.4725 | 0.7956 | |
| | 0.6895 | 3.0 | 3036 | 0.3269 | 0.6694 | 0.7302 | 0.6985 | 0.9044 | |
| | 0.44 | 4.0 | 4048 | 0.1325 | 0.8356 | 0.9091 | 0.8708 | 0.9667 | |
| | 0.2585 | 5.0 | 5060 | 0.0717 | 0.9259 | 0.9531 | 0.9393 | 0.9844 | |
| | 0.1722 | 6.0 | 6072 | 0.0382 | 0.9480 | 0.9619 | 0.9549 | 0.99 | |
| | 0.0919 | 7.0 | 7084 | 0.0328 | 0.9539 | 0.9707 | 0.9622 | 0.9911 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.18.0 |
| - Pytorch 1.10.0+cu111 |
| - Datasets 2.1.0 |
| - Tokenizers 0.12.1 |
| |
