| --- |
| license: mit |
| base_model: roberta-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| - f1 |
| model-index: |
| - name: roberta-twitter-hate |
| 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. --> |
|
|
| # roberta-twitter-hate |
|
|
| This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4968 |
| - Accuracy: 0.761 |
| - Precision: 0.6722 |
| - Recall: 0.8595 |
| - F1: 0.7544 |
|
|
| ## 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: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 3 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | No log | 1.0 | 282 | 0.4968 | 0.761 | 0.6722 | 0.8595 | 0.7544 | |
| | 0.425 | 2.0 | 564 | 0.5053 | 0.761 | 0.6767 | 0.8431 | 0.7508 | |
| | 0.425 | 3.0 | 846 | 0.5244 | 0.777 | 0.7082 | 0.8126 | 0.7568 | |
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|
|
| ### Framework versions |
|
|
| - Transformers 4.40.2 |
| - Pytorch 2.7.1+cu126 |
| - Datasets 2.19.1 |
| - Tokenizers 0.19.1 |
|
|
