mt5_base_TH_wiki
This model is a fine-tuned version of google/mt5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Rouge2 Precision: 0.0021
- Rouge2 Recall: 0.0009
- Rouge2 Fmeasure: 0.0013
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: 50
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|---|---|---|---|---|---|---|
| 0.0 | 1.0 | 1296 | nan | 0.0021 | 0.0009 | 0.0013 |
| 0.0 | 2.0 | 2592 | nan | 0.0021 | 0.0009 | 0.0013 |
| 0.0 | 3.0 | 3888 | nan | 0.0021 | 0.0009 | 0.0013 |
| 0.0 | 4.0 | 5184 | nan | 0.0021 | 0.0009 | 0.0013 |
| 0.0 | 5.0 | 6480 | nan | 0.0021 | 0.0009 | 0.0013 |
| 0.0 | 6.0 | 7776 | nan | 0.0021 | 0.0009 | 0.0013 |
| 0.0 | 7.0 | 9072 | nan | 0.0021 | 0.0009 | 0.0013 |
| 0.0 | 8.0 | 10368 | nan | 0.0021 | 0.0009 | 0.0013 |
| 0.0 | 9.0 | 11664 | nan | 0.0021 | 0.0009 | 0.0013 |
| 0.0 | 10.0 | 12960 | nan | 0.0021 | 0.0009 | 0.0013 |
| 0.0 | 11.0 | 14256 | nan | 0.0021 | 0.0009 | 0.0013 |
| 0.0 | 12.0 | 15552 | nan | 0.0021 | 0.0009 | 0.0013 |
| 0.0 | 13.0 | 16848 | nan | 0.0021 | 0.0009 | 0.0013 |
| 0.0 | 14.0 | 18144 | nan | 0.0021 | 0.0009 | 0.0013 |
| 0.0 | 15.0 | 19440 | nan | 0.0021 | 0.0009 | 0.0013 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.2.2
- Datasets 2.16.1
- Tokenizers 0.20.1