EN_t5-base_8_spider
This model is a fine-tuned version of t5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2576
- Rouge2 Precision: 0.5995
- Rouge2 Recall: 0.3907
- Rouge2 Fmeasure: 0.4452
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: 10
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|---|---|---|---|---|---|---|
| 0.5688 | 1.0 | 700 | 0.2352 | 0.5179 | 0.334 | 0.38 |
| 0.1863 | 2.0 | 1400 | 0.2287 | 0.5608 | 0.3634 | 0.4139 |
| 0.1145 | 3.0 | 2100 | 0.2350 | 0.5824 | 0.3758 | 0.4289 |
| 0.1013 | 4.0 | 2800 | 0.2426 | 0.5818 | 0.3713 | 0.4253 |
| 0.0818 | 5.0 | 3500 | 0.2450 | 0.5888 | 0.377 | 0.4313 |
| 0.0729 | 6.0 | 4200 | 0.2507 | 0.5968 | 0.3841 | 0.4393 |
| 0.0693 | 7.0 | 4900 | 0.2545 | 0.5899 | 0.3848 | 0.4384 |
| 0.0635 | 8.0 | 5600 | 0.2576 | 0.5995 | 0.3907 | 0.4452 |
Framework versions
- Transformers 4.26.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.7.dev0
- Tokenizers 0.13.3