metadata
library_name: transformers
base_model: cardiffnlp/twitter-roberta-base-hate
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: test_dir_model3
results: []
test_dir_model3
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: 2.2679
- Accuracy: 0.8783
- F1: 0.6997
- Precision: 0.8118
- Recall: 0.6915
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: 64
- eval_batch_size: 64
- 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: cosine
- num_epochs: 10
- label_smoothing_factor: 0.1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 35 | 1.1935 | 0.7304 | 0.3920 | 0.3732 | 0.4740 |
| No log | 2.0 | 70 | 1.2142 | 0.8348 | 0.6136 | 0.6065 | 0.6625 |
| 0.9237 | 3.0 | 105 | 1.3719 | 0.8783 | 0.7167 | 0.7802 | 0.7244 |
| 0.9237 | 4.0 | 140 | 1.5517 | 0.8696 | 0.7135 | 0.7685 | 0.7367 |
| 0.9237 | 5.0 | 175 | 1.9028 | 0.8870 | 0.7282 | 0.7874 | 0.7423 |
| 0.3387 | 6.0 | 210 | 2.0006 | 0.8696 | 0.6333 | 0.775 | 0.6708 |
| 0.3387 | 7.0 | 245 | 2.1684 | 0.8783 | 0.6997 | 0.8118 | 0.6915 |
| 0.3387 | 8.0 | 280 | 2.1672 | 0.8696 | 0.6958 | 0.7972 | 0.7038 |
| 0.119 | 9.0 | 315 | 2.2526 | 0.8783 | 0.6997 | 0.8118 | 0.6915 |
| 0.119 | 10.0 | 350 | 2.2679 | 0.8783 | 0.6997 | 0.8118 | 0.6915 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1