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t5_finetuned_genboolq
This model is a fine-tuned version of t5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5011
- Rouge1: 36.4881
- Rouge2: 17.8649
- Rougel: 34.2658
- Rougelsum: 34.2336
- Gen Len: 11.7003
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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 0.5854 | 1.0 | 2082 | 0.5182 | 35.5544 | 16.9686 | 33.3783 | 33.3536 | 11.5918 |
| 0.5479 | 2.0 | 4164 | 0.4969 | 37.0664 | 18.2443 | 34.7139 | 34.6934 | 11.8662 |
| 0.5405 | 3.0 | 6246 | 0.5011 | 36.4881 | 17.8649 | 34.2658 | 34.2336 | 11.7003 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
