roberta-fa-zwnj-base-finetuned-IR_sum_QA
This model is a fine-tuned version of HooshvareLab/roberta-fa-zwnj-base on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6340
- {'exact_match': 62.9, 'f1': 68.2213197404294}
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: 16
- eval_batch_size: 16
- 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: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
- fp16 = True
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
| 1.3076 |
1.0 |
1681 |
1.7094 |
| 0.815 |
2.0 |
3362 |
1.5745 |
| 0.5349 |
3.0 |
5043 |
1.6340 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1