| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: t5-small |
| tags: |
| - simplification |
| - generated_from_trainer |
| metrics: |
| - bleu |
| model-index: |
| - name: t5-neutralisation |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # t5-neutralisation |
|
|
| This model is a fine-tuned version of [t5-small](https://huggingface.co/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 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.51.2 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.0.0 |
| - Tokenizers 0.21.4 |
|
|
