t5-small-finetuned-EdinburghNLP-xsum
This model is a fine-tuned version of google-t5/t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.4551
- Rouge1: 29.0623
- Rouge2: 8.6688
- Rougel: 23.99
- Rougelsum: 23.9849
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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 2.6650 | 1.0 | 3814 | 2.5130 | 28.4559 | 8.234 | 23.4457 | 23.4492 |
| 2.6507 | 2.0 | 7628 | 2.4654 | 28.901 | 8.5041 | 23.8272 | 23.8284 |
| 2.6006 | 3.0 | 11442 | 2.4551 | 29.0623 | 8.6688 | 23.99 | 23.9849 |
Framework versions
- Transformers 5.16.1
- Pytorch 2.11.0+cu128
- Datasets 4.8.5
- Tokenizers 0.23.1