| | --- |
| | license: apache-2.0 |
| | base_model: google-t5/t5-small |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - bleu |
| | model-index: |
| | - name: ft-wmt14 |
| | 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. --> |
| |
|
| | # ft-wmt14 |
| |
|
| | This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.7607 |
| | - Bleu: 23.421 |
| | - Gen Len: 27.6243 |
| |
|
| | ## 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: 0.0005 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 16 |
| | - optimizer: Adafactor |
| | - lr_scheduler_type: linear |
| | - training_steps: 100000 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |
| | |:-------------:|:------:|:------:|:---------------:|:-------:|:-------:| |
| | | 1.7882 | 0.2778 | 10000 | 1.9278 | 19.7853 | 28.4147 | |
| | | 1.6619 | 0.5556 | 20000 | 1.8710 | 21.3803 | 27.667 | |
| | | 1.6007 | 0.8333 | 30000 | 1.8397 | 22.2715 | 27.317 | |
| | | 1.5269 | 1.1111 | 40000 | 1.8205 | 21.9329 | 27.704 | |
| | | 1.498 | 1.3889 | 50000 | 1.8134 | 22.4836 | 27.63 | |
| | | 1.4801 | 1.6667 | 60000 | 1.7941 | 22.727 | 27.582 | |
| | | 1.462 | 1.9444 | 70000 | 1.7766 | 23.0372 | 27.5903 | |
| | | 1.4182 | 2.2222 | 80000 | 1.7724 | 23.6231 | 27.4233 | |
| | | 1.4079 | 2.5 | 90000 | 1.7663 | 23.2604 | 27.7623 | |
| | | 1.4037 | 2.7778 | 100000 | 1.7607 | 23.421 | 27.6243 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.40.0 |
| | - Pytorch 2.2.2+cu121 |
| | - Datasets 2.19.0 |
| | - Tokenizers 0.19.1 |
| | |
