t5-small-finetuned-xsum
This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2612
- Rouge1: 0.1351
- Rouge2: 0.0901
- Rougel: 0.1351
- Rougelsum: 0.1351
- Gen Len: 20.0
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: 4
- eval_batch_size: 4
- 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: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 0.2617 | 1.0 | 833 | 0.2698 | 1.4344 | 0.6532 | 1.5148 | 1.4595 | 20.0 |
| 0.2891 | 2.0 | 1666 | 0.2693 | 0.5721 | 0.2252 | 0.5856 | 0.5495 | 20.0 |
| 0.2887 | 3.0 | 2499 | 0.2621 | 0.1802 | 0.0901 | 0.1952 | 0.1952 | 20.0 |
| 0.2881 | 4.0 | 3332 | 0.2623 | 0.1351 | 0.0901 | 0.1351 | 0.1351 | 20.0 |
| 0.2829 | 5.0 | 4165 | 0.2620 | 0.1351 | 0.0901 | 0.1351 | 0.1351 | 20.0 |
| 0.3004 | 6.0 | 4998 | 0.2612 | 0.1351 | 0.0901 | 0.1351 | 0.1351 | 20.0 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0