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le-fine-tune-mt5-base
This model is a fine-tuned version of google/mt5-base on the ravkuk_summerize_dataset dataset. It achieves the following results on the evaluation set:
- Loss: 2.6590
- Rouge1: 0.1555
- Rouge2: 0.065
- Rougel: 0.1489
- Rougelsum: 0.149
- Gen Len: 18.9858
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 |
|---|---|---|---|---|---|---|---|---|
| 5.0797 | 1.0 | 197 | 2.7316 | 0.1101 | 0.0319 | 0.1025 | 0.1024 | 18.9432 |
| 2.8975 | 2.0 | 394 | 2.6943 | 0.1239 | 0.0453 | 0.1207 | 0.1204 | 18.9688 |
| 2.7115 | 3.0 | 591 | 2.6143 | 0.1333 | 0.0505 | 0.1283 | 0.1289 | 18.9688 |
| 2.365 | 4.0 | 788 | 2.5704 | 0.125 | 0.0433 | 0.1201 | 0.1199 | 19.0 |
| 2.0738 | 5.0 | 985 | 2.5296 | 0.1341 | 0.0478 | 0.1284 | 0.1286 | 18.9858 |
| 1.6716 | 6.0 | 1182 | 2.4902 | 0.1451 | 0.0554 | 0.1397 | 0.1395 | 18.9886 |
| 1.2644 | 7.0 | 1379 | 2.5039 | 0.1446 | 0.0562 | 0.1407 | 0.1406 | 18.9744 |
| 0.9641 | 8.0 | 1576 | 2.6590 | 0.1555 | 0.065 | 0.1489 | 0.149 | 18.9858 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
