| --- |
| library_name: transformers |
| base_model: cardiffnlp/twitter-roberta-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| - accuracy |
| - precision |
| - recall |
| model-index: |
| - name: sarcasm-detector-roberta |
| 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. --> |
|
|
| # sarcasm-detector-roberta |
|
|
| This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base](https://huggingface.co/cardiffnlp/twitter-roberta-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6026 |
| - F1: 0.7528 |
| - Accuracy: 0.7538 |
| - Precision: 0.7633 |
| - Recall: 0.7734 |
|
|
| ## 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: 1e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 5 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | Precision | Recall | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:|:------:| |
| | 0.5678 | 1.0 | 179 | 0.6256 | 0.6490 | 0.6555 | 0.6808 | 0.6630 | |
| | 0.5366 | 2.0 | 358 | 0.5578 | 0.7204 | 0.7204 | 0.7211 | 0.7214 | |
| | 0.4206 | 3.0 | 537 | 0.6071 | 0.7214 | 0.7215 | 0.7221 | 0.7224 | |
| | 0.3041 | 4.0 | 716 | 0.6764 | 0.7338 | 0.7340 | 0.7391 | 0.7369 | |
| | 0.3386 | 5.0 | 895 | 0.6968 | 0.7298 | 0.7298 | 0.7316 | 0.7315 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.6.2 |
| - Pytorch 2.11.0+cu130 |
| - Datasets 4.8.5 |
| - Tokenizers 0.22.2 |
| |
