t5-base-task2
This model is a fine-tuned version of google-t5/t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.4722
- Rouge L: 29.3763
- Bleu-4: 10.6675
- Bertscore F1: 87.2021
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge L | Bleu-4 | Bertscore F1 |
|---|---|---|---|---|---|---|
| No log | 1.0 | 246 | 2.6005 | 27.3895 | 9.3023 | 86.8290 |
| No log | 2.0 | 492 | 2.5068 | 28.0500 | 9.8400 | 87.0370 |
| 2.6687 | 3.0 | 738 | 2.4763 | 28.8285 | 10.1972 | 87.0570 |
| 2.6687 | 4.0 | 984 | 2.4722 | 29.3763 | 10.6675 | 87.2021 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0