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t5-base-finetuned-qg-context-dataset
This model is a fine-tuned version of t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6222
- Rouge1: 36.2283
- Rouge2: 16.0636
- Rougel: 32.6282
- Rougelsum: 32.6551
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 73 | 1.8864 | 32.9447 | 13.9495 | 27.5473 | 27.4092 |
| No log | 2.0 | 146 | 1.6866 | 35.1131 | 13.7925 | 30.7017 | 30.5957 |
| No log | 3.0 | 219 | 1.6392 | 30.4209 | 11.2611 | 27.0456 | 27.0847 |
| No log | 4.0 | 292 | 1.6222 | 36.2283 | 16.0636 | 32.6282 | 32.6551 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.2
