t5-small-finetuned-xsum
This model is a fine-tuned version of t5-small on the xsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.3878
- Rouge1: 29.5769
- Rouge2: 8.7047
- Rougel: 23.446
- Rougelsum: 23.4444
- Gen Len: 18.8262
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 |
|---|---|---|---|---|---|---|---|---|
| 2.6682 | 1.0 | 12753 | 2.4400 | 28.7524 | 8.1221 | 22.6965 | 22.6964 | 18.8131 |
| 2.6078 | 2.0 | 25506 | 2.4006 | 29.4484 | 8.5941 | 23.308 | 23.3037 | 18.8087 |
| 2.6137 | 3.0 | 38259 | 2.3878 | 29.5769 | 8.7047 | 23.446 | 23.4444 | 18.8262 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
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Base model
google-t5/t5-small