t5-small-finetuned-NL2ModelioMQ
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0755
- Rouge2 Precision: 0.7481
- Rouge2 Recall: 0.462
- Rouge2 Fmeasure: 0.5577
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: 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 | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|---|---|---|---|---|---|---|
| No log | 1.0 | 449 | 0.1696 | 0.6061 | 0.3886 | 0.4635 |
| 0.653 | 2.0 | 898 | 0.0933 | 0.7231 | 0.4496 | 0.5415 |
| 0.2028 | 3.0 | 1347 | 0.0755 | 0.7481 | 0.462 | 0.5577 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2