metadata
library_name: transformers
license: mit
base_model: cardiffnlp/twitter-roberta-large-hate-latest
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: twitter-roberta-large-hate-latest-offensive-eval-kn
results: []
twitter-roberta-large-hate-latest-offensive-eval-kn
This model is a fine-tuned version of cardiffnlp/twitter-roberta-large-hate-latest on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8543
- Accuracy: 0.7391
- Precision: 0.4215
- Recall: 0.3968
- F1: 0.4020
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: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.9082 | 0.9968 | 157 | 0.8529 | 0.7286 | 0.3746 | 0.3354 | 0.3312 |
| 0.7593 | 2.0 | 315 | 0.7818 | 0.7393 | 0.5160 | 0.3778 | 0.3767 |
| 0.7264 | 2.9968 | 472 | 0.7640 | 0.7464 | 0.4450 | 0.3812 | 0.3861 |
| 0.6998 | 4.0 | 630 | 0.7941 | 0.7464 | 0.4461 | 0.4106 | 0.4218 |
| 0.5066 | 4.9968 | 787 | 0.8636 | 0.7518 | 0.4668 | 0.4156 | 0.4276 |
| 0.5164 | 6.0 | 945 | 0.8747 | 0.7482 | 0.4391 | 0.4342 | 0.4342 |
| 0.4098 | 6.9968 | 1102 | 0.9078 | 0.7446 | 0.4366 | 0.4324 | 0.4334 |
| 0.3556 | 8.0 | 1260 | 0.9286 | 0.7393 | 0.4279 | 0.4304 | 0.4282 |
| 0.3974 | 8.9968 | 1417 | 0.9444 | 0.7446 | 0.4434 | 0.4406 | 0.4411 |
| 0.318 | 9.9683 | 1570 | 0.9597 | 0.7411 | 0.4352 | 0.4370 | 0.4352 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0