t5-neutralisation
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0593
- Bleu: 54.7416
- Gen Len: 18.7292
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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| No log | 1.0 | 440 | 0.0837 | 53.9225 | 18.6042 |
| 0.0369 | 2.0 | 880 | 0.0739 | 54.1449 | 18.6354 |
| 0.034 | 3.0 | 1320 | 0.0690 | 54.4631 | 18.6562 |
| 0.0346 | 4.0 | 1760 | 0.0625 | 54.7416 | 18.7292 |
| 0.0423 | 5.0 | 2200 | 0.0599 | 54.7416 | 18.7292 |
| 0.0406 | 6.0 | 2640 | 0.0593 | 54.7416 | 18.7292 |
Framework versions
- Transformers 4.51.2
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.21.4
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Base model
google-t5/t5-small