mt5-small-asqp-rest16
This model is a fine-tuned version of google/mt5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4146
- Precision: 0.3287
- Recall: 0.4221
- F1: 0.3696
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: 0.0003
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.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
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
|---|---|---|---|---|---|---|
| No log | 1.0 | 79 | 1.7680 | 0.0 | 0.0 | 0 |
| No log | 2.0 | 158 | 0.7157 | 0.0877 | 0.0986 | 0.0929 |
| No log | 3.0 | 237 | 0.5655 | 0.0915 | 0.2071 | 0.127 |
| No log | 4.0 | 316 | 0.4808 | 0.2169 | 0.2682 | 0.2399 |
| No log | 5.0 | 395 | 0.4643 | 0.16 | 0.3412 | 0.2179 |
| No log | 6.0 | 474 | 0.4340 | 0.2551 | 0.3669 | 0.301 |
| 2.1045 | 7.0 | 553 | 0.4385 | 0.2283 | 0.3787 | 0.2849 |
| 2.1045 | 8.0 | 632 | 0.4229 | 0.2456 | 0.3846 | 0.2998 |
| 2.1045 | 9.0 | 711 | 0.4244 | 0.317 | 0.3945 | 0.3515 |
| 2.1045 | 10.0 | 790 | 0.4190 | 0.3296 | 0.4024 | 0.3623 |
| 2.1045 | 11.0 | 869 | 0.4211 | 0.3243 | 0.4004 | 0.3583 |
| 2.1045 | 12.0 | 948 | 0.4274 | 0.3069 | 0.4122 | 0.3519 |
| 0.3564 | 13.0 | 1027 | 0.4162 | 0.3209 | 0.4083 | 0.3594 |
| 0.3564 | 14.0 | 1106 | 0.4131 | 0.3365 | 0.4221 | 0.3745 |
| 0.3564 | 15.0 | 1185 | 0.4146 | 0.3287 | 0.4221 | 0.3696 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1