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le-fine-tune-mt5-small
This model is a fine-tuned version of google/mt5-small on the ravkuk_summerize_dataset dataset. It achieves the following results on the evaluation set:
- Loss: 2.4588
- Rouge1: 0.16
- Rouge2: 0.0655
- Rougel: 0.1519
- Rougelsum: 0.1522
- Gen Len: 18.9886
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: 0.0014142135623730952
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.3
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 7.6563 | 1.0 | 197 | 3.0371 | 0.1002 | 0.028 | 0.0941 | 0.0941 | 18.8949 |
| 3.4565 | 2.0 | 394 | 2.8403 | 0.1204 | 0.0362 | 0.1154 | 0.1152 | 18.9744 |
| 3.0924 | 3.0 | 591 | 2.7173 | 0.1276 | 0.0431 | 0.1199 | 0.1202 | 18.9631 |
| 2.7357 | 4.0 | 788 | 2.5831 | 0.1494 | 0.0555 | 0.1415 | 0.1416 | 18.9744 |
| 2.4543 | 5.0 | 985 | 2.5135 | 0.1437 | 0.0545 | 0.1345 | 0.135 | 18.9886 |
| 2.2055 | 6.0 | 1182 | 2.5031 | 0.1544 | 0.0642 | 0.147 | 0.1472 | 18.9773 |
| 2.0147 | 7.0 | 1379 | 2.4554 | 0.158 | 0.0643 | 0.1484 | 0.1487 | 18.9688 |
| 1.8746 | 8.0 | 1576 | 2.4588 | 0.16 | 0.0655 | 0.1519 | 0.1522 | 18.9886 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
