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: 0.3233
- Rouge1: 46.8426
- Rouge2: 0.4676
- Rougel: 46.6278
- Rougelsum: 46.631
- Gen Len: 19.0
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: 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 |
|---|---|---|---|---|---|---|---|---|
| 0.3816 | 1.0 | 779 | 0.3233 | 46.8426 | 0.4676 | 46.6278 | 46.631 | 19.0 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0
- Datasets 3.3.2
- Tokenizers 0.15.0
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Model tree for Slowin/t5-small-finetuned-xsum
Base model
google-t5/t5-small