jackmedda/google-long-t5-tglobal-base_finetuned_augmented_augmented_qwen2.5_72b
This model is a fine-tuned version of google/long-t5-tglobal-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5751
- Accuracy: 0.7647
- F1: 0.8667
- Precision: 0.7647
- Recall: 1.0
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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- 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: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.6164 | 1.0 | 92 | 0.6295 | 0.7 | 0.8235 | 0.7 | 1.0 |
| 0.441 | 2.0 | 184 | 1.0194 | 0.7 | 0.8235 | 0.7 | 1.0 |
| 0.5682 | 3.0 | 276 | 1.5109 | 0.7 | 0.8235 | 0.7 | 1.0 |
| 1.0803 | 4.0 | 368 | 1.6351 | 0.7 | 0.8235 | 0.7 | 1.0 |
| 0.9585 | 5.0 | 460 | 1.7171 | 0.7 | 0.8235 | 0.7 | 1.0 |
| 0.2445 | 6.0 | 552 | 1.7306 | 0.7 | 0.8235 | 0.7 | 1.0 |
| 0.7548 | 7.0 | 644 | 1.7669 | 0.7 | 0.8235 | 0.7 | 1.0 |
| 0.0069 | 8.0 | 736 | 1.7511 | 0.7 | 0.8235 | 0.7 | 1.0 |
| 0.499 | 9.0 | 828 | 1.7201 | 0.7 | 0.8235 | 0.7 | 1.0 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.3.0+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0