t5-base-finetuned
This model is a fine-tuned version of t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5898
- Rouge1: 17.2165
- Rouge2: 11.8708
- Rougel: 16.3268
- Rougelsum: 17.0186
- Gen Len: 18.9742
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: 0.0002
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use 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: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 0.7425 | 1.0 | 2201 | 0.6120 | 17.1271 | 11.7087 | 16.1905 | 16.9211 | 18.9732 |
| 0.6531 | 2.0 | 4402 | 0.5898 | 17.2165 | 11.8708 | 16.3268 | 17.0186 | 18.9742 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3
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Model tree for the-derex/t5-base-finetuned
Base model
google-t5/t5-base