| --- |
| license: mit |
| base_model: FacebookAI/roberta-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: model |
| 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. --> |
|
|
| # model |
|
|
| This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6917 |
| - Precision: 0.7168 |
| - Recall: 0.7053 |
| - F1: 0.7088 |
| - Accuracy: 0.726 |
|
|
| ## 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 |
| - num_epochs: 5 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | 0.9791 | 1.0 | 1489 | 0.8084 | 0.6198 | 0.6089 | 0.6093 | 0.6385 | |
| | 0.8129 | 2.0 | 2978 | 0.7380 | 0.6635 | 0.6500 | 0.6531 | 0.6735 | |
| | 0.6937 | 3.0 | 4467 | 0.7328 | 0.6826 | 0.6716 | 0.6745 | 0.691 | |
| | 0.6002 | 4.0 | 5956 | 0.6901 | 0.7110 | 0.6951 | 0.6973 | 0.7205 | |
| | 0.5362 | 5.0 | 7445 | 0.6917 | 0.7168 | 0.7053 | 0.7088 | 0.726 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.40.0 |
| - Pytorch 2.2.1+cu121 |
| - Datasets 2.19.0 |
| - Tokenizers 0.19.1 |
|
|
