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model
This model is a fine-tuned version of roberta-large on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 0.5350
- Precision: 0.5932
- Recall: 0.7371
- F1: 0.6574
- Accuracy: 0.8967
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 0.47 | 466 | 0.5513 | 0.5389 | 0.7358 | 0.6222 | 0.8787 |
| 0.4041 | 1.47 | 932 | 0.5179 | 0.5398 | 0.7613 | 0.6317 | 0.8797 |
| 0.3968 | 2.07 | 1000 | 0.5350 | 0.5932 | 0.7371 | 0.6574 | 0.8967 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
