| --- |
| license: apache-2.0 |
| base_model: google-bert/bert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| model-index: |
| - name: fine_tuned_cb_bert |
| 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. --> |
|
|
| # fine_tuned_cb_bert |
| |
| This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 4.2169 |
| - Accuracy: 0.3636 |
| - F1: 0.2430 |
| |
| ## 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 |
| - training_steps: 400 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| |:-------------:|:-------:|:----:|:---------------:|:--------:|:------:| |
| | 0.7239 | 3.5714 | 50 | 1.2945 | 0.3182 | 0.1536 | |
| | 0.3879 | 7.1429 | 100 | 1.6236 | 0.4545 | 0.4158 | |
| | 0.1546 | 10.7143 | 150 | 3.1975 | 0.3636 | 0.2430 | |
| | 0.0741 | 14.2857 | 200 | 2.9703 | 0.4545 | 0.3895 | |
| | 0.0323 | 17.8571 | 250 | 3.8104 | 0.3636 | 0.2430 | |
| | 0.0073 | 21.4286 | 300 | 4.0583 | 0.3636 | 0.2430 | |
| | 0.0037 | 25.0 | 350 | 4.3166 | 0.3636 | 0.2430 | |
| | 0.0032 | 28.5714 | 400 | 4.2169 | 0.3636 | 0.2430 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.40.1 |
| - Pytorch 2.3.0 |
| - Datasets 2.19.0 |
| - Tokenizers 0.19.1 |
| |
