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t5-large-qa-for-fewshot
This model is a fine-tuned version of t5-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1275
- Rouge1: 78.0444
- Rouge2: 66.6789
- Rougel: 77.4324
- Rougelsum: 77.4473
- 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 306 | 0.1277 | 77.6808 | 66.4634 | 77.0694 | 77.0872 | 19.0 |
| 0.1758 | 2.0 | 612 | 0.1275 | 78.0444 | 66.6789 | 77.4324 | 77.4473 | 19.0 |
| 0.1758 | 3.0 | 918 | 0.1310 | 78.4815 | 68.3121 | 78.0501 | 78.0194 | 19.0 |
| 0.0786 | 4.0 | 1224 | 0.1413 | 78.3183 | 67.4242 | 77.7702 | 77.7753 | 19.0 |
| 0.0465 | 5.0 | 1530 | 0.1535 | 78.2176 | 67.4929 | 77.6782 | 77.6628 | 19.0 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
