metadata
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-twitter-hate
results: []
roberta-twitter-hate
This model is a fine-tuned version of 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 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.7.1+cu126
- Datasets 2.19.1
- Tokenizers 0.19.1