| | --- |
| | license: apache-2.0 |
| | base_model: google/mt5-small |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - wer |
| | model-index: |
| | - name: mt5-base |
| | 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. --> |
| |
|
| | # mt5-base |
| |
|
| | This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0516 |
| | - Wer: 0.0392 |
| |
|
| | ## 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: 0.0003 |
| | - train_batch_size: 4 |
| | - eval_batch_size: 4 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 2000 |
| | - num_epochs: 10 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Wer | |
| | |:-------------:|:-----:|:-----:|:---------------:|:------:| |
| | | 3.4396 | 0.81 | 4000 | 0.3368 | 0.3043 | |
| | | 0.4257 | 1.62 | 8000 | 0.1328 | 0.1205 | |
| | | 0.2185 | 2.42 | 12000 | 0.0929 | 0.0879 | |
| | | 0.1506 | 3.23 | 16000 | 0.0762 | 0.0708 | |
| | | 0.1133 | 4.04 | 20000 | 0.0663 | 0.0587 | |
| | | 0.092 | 4.85 | 24000 | 0.0620 | 0.0551 | |
| | | 0.0739 | 5.66 | 28000 | 0.0583 | 0.0507 | |
| | | 0.0649 | 6.46 | 32000 | 0.0572 | 0.0465 | |
| | | 0.0564 | 7.27 | 36000 | 0.0545 | 0.0439 | |
| | | 0.0494 | 8.08 | 40000 | 0.0533 | 0.0425 | |
| | | 0.0433 | 8.89 | 44000 | 0.0522 | 0.0405 | |
| | | 0.0396 | 9.7 | 48000 | 0.0516 | 0.0392 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.33.0 |
| | - Pytorch 2.0.0 |
| | - Datasets 2.1.0 |
| | - Tokenizers 0.13.3 |
| | |
