T5_small_fine_tuned
This model is a fine-tuned version of google-t5/t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.6491
- Rougel Fmeasure: 0.1247
- Bertscore F1: -0.0215
- Combined Score: 0.0516
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: 8
- eval_batch_size: 8
- 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: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rougel Fmeasure | Bertscore F1 | Combined Score |
|---|---|---|---|---|---|---|
| 1.9205 | 1.0 | 2369 | 2.6825 | 0.113 | -0.0448 | 0.0341 |
| 1.8233 | 2.0 | 4738 | 2.6561 | 0.1227 | -0.0249 | 0.0489 |
| 1.7693 | 3.0 | 7107 | 2.6505 | 0.1246 | -0.0215 | 0.0515 |
| 1.7611 | 4.0 | 9476 | 2.6491 | 0.1247 | -0.0215 | 0.0516 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
google-t5/t5-small