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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: 0.0162
- Rouge1: 98.555
- Rouge2: 97.81
- Rougel: 98.5536
- Rougelsum: 98.557
- Gen Len: 9.851
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 0.0416 | 1.0 | 5986 | 0.0238 | 98.3612 | 97.6286 | 98.3553 | 98.3578 | 9.8923 |
| 0.0229 | 2.0 | 11972 | 0.0179 | 98.4752 | 97.7159 | 98.4754 | 98.4757 | 9.8488 |
| 0.0201 | 3.0 | 17958 | 0.0162 | 98.555 | 97.81 | 98.5536 | 98.557 | 9.851 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.2
- Tokenizers 0.13.3
