t5small_cnndailymail
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.8689
- Rouge1: 0.4195
- Rouge2: 0.1951
- Rougel: 0.2930
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: 0.0003
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.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: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel |
|---|---|---|---|---|---|---|
| No log | 1.0 | 313 | 1.8715 | 0.4151 | 0.1902 | 0.2884 |
| 4.0892 | 2.0 | 626 | 1.8599 | 0.4194 | 0.1967 | 0.2925 |
| 4.0892 | 3.0 | 939 | 1.8650 | 0.4176 | 0.1954 | 0.2920 |
| 3.8640 | 4.0 | 1252 | 1.8609 | 0.4191 | 0.1950 | 0.2923 |
| 3.7480 | 5.0 | 1565 | 1.8689 | 0.4195 | 0.1951 | 0.2930 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2