| --- |
| license: apache-2.0 |
| base_model: bert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| - accuracy |
| - precision |
| - recall |
| model-index: |
| - name: rating-classifier |
| 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. --> |
|
|
| # rating-classifier |
|
|
| 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: |
| - F1: 0.6729 |
| - Loss: 0.8373 |
| - Accuracy: 0.6710 |
| - Precision: 0.6774 |
| - Recall: 0.6710 |
|
|
| ## 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 |
| - lr_scheduler_warmup_steps: 500 |
| - num_epochs: 5 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | F1 | Validation Loss | Accuracy | Precision | Recall | |
| |:-------------:|:-----:|:----:|:------:|:---------------:|:--------:|:---------:|:------:| |
| | 1.0326 | 1.0 | 984 | 0.6354 | 0.8096 | 0.6707 | 0.6383 | 0.6707 | |
| | 0.6801 | 2.0 | 1968 | 0.6668 | 0.7508 | 0.6888 | 0.6667 | 0.6888 | |
| | 0.5313 | 3.0 | 2952 | 0.6729 | 0.8373 | 0.6710 | 0.6774 | 0.6710 | |
| | 0.3895 | 4.0 | 3936 | 0.6678 | 0.9705 | 0.6730 | 0.6649 | 0.6730 | |
| | 0.2857 | 5.0 | 4920 | 0.6708 | 1.0989 | 0.6745 | 0.6684 | 0.6745 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.42.4 |
| - Pytorch 2.3.1+cu121 |
| - Datasets 2.21.0 |
| - Tokenizers 0.19.1 |
| |
