metadata
library_name: transformers
base_model: cardiffnlp/twitter-roberta-base-hate
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: twitter-roberta-base-hate_42
results: []
twitter-roberta-base-hate_42
This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-hate on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4071
- F1-score: 0.8447
- Accuracy: 0.8462
- Precision: 0.8436
- Recall: 0.8465
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: 5e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | F1-score | Accuracy | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 180 | 0.3830 | 0.8243 | 0.8252 | 0.8241 | 0.8286 |
| No log | 2.0 | 360 | 0.3669 | 0.8312 | 0.8322 | 0.8305 | 0.8348 |
| 0.3605 | 3.0 | 540 | 0.3820 | 0.8246 | 0.8252 | 0.8256 | 0.8303 |
| 0.3605 | 4.0 | 720 | 0.3968 | 0.8410 | 0.8427 | 0.8401 | 0.8425 |
| 0.3605 | 5.0 | 900 | 0.4079 | 0.8408 | 0.8427 | 0.8401 | 0.8417 |
| 0.2446 | 6.0 | 1080 | 0.4071 | 0.8447 | 0.8462 | 0.8436 | 0.8465 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0