roberta-base-dirQ-v1
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2229
- Precision: 0.8216
- Recall: 0.9257
- F1: 0.8705
- Accuracy: 0.9316
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-05
- train_batch_size: 16
- eval_batch_size: 16
- 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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.3481 | 1.0 | 976 | 0.2343 | 0.8003 | 0.9209 | 0.8564 | 0.9248 |
| 0.1966 | 2.0 | 1952 | 0.2164 | 0.8124 | 0.9217 | 0.8636 | 0.9292 |
| 0.1702 | 3.0 | 2928 | 0.2229 | 0.8216 | 0.9257 | 0.8705 | 0.9316 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1