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: 3.2350
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: 7
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.229 | 0.1001 | 71 | 3.5533 |
| 3.8218 | 0.2003 | 142 | 3.3962 |
| 3.6384 | 0.3004 | 213 | 3.3290 |
| 3.6616 | 0.4006 | 284 | 3.2940 |
| 3.5887 | 0.5007 | 355 | 3.2713 |
| 3.6246 | 0.6008 | 426 | 3.2550 |
| 3.5184 | 0.7010 | 497 | 3.2448 |
| 3.5059 | 0.8011 | 568 | 3.2391 |
| 3.5116 | 0.9013 | 639 | 3.2350 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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google-t5/t5-small