t5-small-finetuned-xsum
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.5068
- Rouge1: 9.6685
- Rouge2: 4.7474
- Rougel: 8.1471
- Rougelsum: 8.1134
- Gen Len: 12.0975
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: 16
- 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: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 25 | 5.0364 | 8.8443 | 4.253 | 7.387 | 7.3495 | 11.6375 |
| No log | 2.0 | 50 | 4.6148 | 9.3918 | 4.554 | 7.8807 | 7.8583 | 11.8975 |
| No log | 3.0 | 75 | 4.5068 | 9.6685 | 4.7474 | 8.1471 | 8.1134 | 12.0975 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0