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t5-small-finetuned-xsum-512
This model is a fine-tuned version of t5-small on the xsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.4706
- Rouge1: 28.8448
- Rouge2: 7.9819
- Rougel: 22.8686
- Rougelsum: 22.8754
- Gen Len: 18.7654
T5, zero-shot on the same evaluation set:
{'rouge1': 19.2304, 'rouge2': 2.5842, 'rougeL': 13.9683, 'rougeLsum': 15.516}
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: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.7057 | 1.0 | 7854 | 2.4706 | 28.8448 | 7.9819 | 22.8686 | 22.8754 | 18.7654 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.2
- Datasets 2.1.0
- Tokenizers 0.12.1
