t5-small-finetuned-xsum
This model is a fine-tuned version of t5-small on the None dataset.
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: Use OptimizerNames.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: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 1 | 4.5099 | 21.3714 | 12.4743 | 18.5076 | 19.6605 | 19.0 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cpu
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for nahidcs/t5-small-finetuned-xsum
Base model
google-t5/t5-small