t5-large_readme_summarization
This model is a fine-tuned version of t5-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.7393
- Rouge1: 0.4806
- Rouge2: 0.3307
- Rougel: 0.4559
- Rougelsum: 0.4552
- Gen Len: 13.8969
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 1.968 | 1.0 | 2916 | 1.8066 | 0.4624 | 0.3113 | 0.4349 | 0.4342 | 14.0995 |
| 1.8681 | 2.0 | 5832 | 1.7578 | 0.4791 | 0.327 | 0.453 | 0.4526 | 13.8046 |
| 1.875 | 3.0 | 8748 | 1.7441 | 0.479 | 0.3291 | 0.4536 | 0.4536 | 13.8909 |
| 1.8169 | 4.0 | 11664 | 1.7393 | 0.4806 | 0.3307 | 0.4559 | 0.4552 | 13.8969 |
Framework versions
- Transformers 4.35.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
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Base model
google-t5/t5-large