fine_tuned_t5_small_model_sec_5_v13
This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.9971
- Rouge1: 0.4057
- Rouge2: 0.155
- Rougel: 0.2516
- Rougelsum: 0.252
- Gen Len: 95.1
- Bert F1: 0.8758
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: 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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Bert F1 |
|---|---|---|---|---|---|---|---|---|---|
| 3.5508 | 1.0 | 95 | 3.1502 | 0.4016 | 0.1522 | 0.2479 | 0.2476 | 97.6526 | 0.874 |
| 3.1904 | 2.0 | 190 | 3.0374 | 0.4094 | 0.1578 | 0.2536 | 0.2536 | 97.6474 | 0.8757 |
| 3.138 | 3.0 | 285 | 3.0059 | 0.4034 | 0.1538 | 0.2486 | 0.2491 | 95.0211 | 0.8752 |
| 3.1061 | 4.0 | 380 | 2.9971 | 0.4057 | 0.155 | 0.2516 | 0.252 | 95.1 | 0.8758 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.3