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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: 0.6799
- Rouge1: 16.5588
- Rouge2: 10.1416
- Rougel: 15.5658
- Rougelsum: 15.5525
- 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: 0.002
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- gradient_accumulation_steps: 5
- total_train_batch_size: 50
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
No log | 1.0 | 180 | 2.0606 | 12.0435 | 4.427 | 10.6651 | 10.6054 | 18.888 |
No log | 2.0 | 360 | 1.4788 | 17.2418 | 9.6974 | 16.1178 | 16.1121 | 19.0 |
2.5647 | 3.0 | 540 | 1.2028 | 16.3251 | 9.0308 | 15.2903 | 15.2937 | 19.0 |
2.5647 | 4.0 | 720 | 1.0332 | 16.3718 | 9.5348 | 15.3831 | 15.3778 | 19.0 |
2.5647 | 5.0 | 900 | 0.9030 | 16.5137 | 9.7914 | 15.5124 | 15.5142 | 19.0 |
1.1692 | 6.0 | 1080 | 0.8346 | 16.82 | 10.2316 | 15.7513 | 15.7496 | 19.0 |
1.1692 | 7.0 | 1260 | 0.7406 | 16.6103 | 9.8786 | 15.5361 | 15.5297 | 19.0 |
1.1692 | 8.0 | 1440 | 0.6799 | 16.5588 | 10.1416 | 15.5658 | 15.5525 | 19.0 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2