| | --- |
| | language: |
| | - th |
| | license: apache-2.0 |
| | base_model: openai/whisper-small |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - mozilla-foundation/common_voice_17_0 |
| | metrics: |
| | - wer |
| | model-index: |
| | - name: Whisper Small Th |
| | results: |
| | - task: |
| | name: Automatic Speech Recognition |
| | type: automatic-speech-recognition |
| | dataset: |
| | name: Common Voice 17.0 |
| | type: mozilla-foundation/common_voice_17_0 |
| | config: th |
| | split: invalidated |
| | args: 'config: th, split: validated' |
| | metrics: |
| | - name: Wer |
| | type: wer |
| | value: 1.035621009866512 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # Whisper Small Th |
| |
|
| | This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 17.0 dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.5440 |
| | - Wer: 1.0356 |
| |
|
| | ## 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: 1e-05 |
| | - train_batch_size: 16 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 500 |
| | - training_steps: 4000 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Wer | |
| | |:-------------:|:------:|:----:|:---------------:|:------:| |
| | | 0.271 | 0.1087 | 1000 | 0.6722 | 0.9915 | |
| | | 0.1989 | 0.2174 | 2000 | 0.6011 | 1.0015 | |
| | | 0.1557 | 0.3262 | 3000 | 0.5610 | 0.9642 | |
| | | 0.1744 | 0.4349 | 4000 | 0.5440 | 1.0356 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.44.0 |
| | - Pytorch 2.4.0+cu121 |
| | - Datasets 2.20.0 |
| | - Tokenizers 0.19.1 |
| | |
