| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: openai/whisper-tiny |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - audiofolder |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: whisper-tiny-tamil |
| | results: |
| | - task: |
| | name: Audio Classification |
| | type: audio-classification |
| | dataset: |
| | name: Speech Commands |
| | type: audiofolder |
| | config: default |
| | split: train |
| | args: default |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.7142857142857143 |
| | --- |
| | |
| | <!-- 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-tiny-tamil |
| |
|
| | This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Speech Commands dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.6296 |
| | - Accuracy: 0.7143 |
| |
|
| | ## 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: 5e-05 |
| | - train_batch_size: 2 |
| | - eval_batch_size: 2 |
| | - 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 |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - num_epochs: 10 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 0.9817 | 1.0 | 55 | 1.0006 | 0.5714 | |
| | | 0.894 | 2.0 | 110 | 0.8903 | 0.5714 | |
| | | 0.7656 | 3.0 | 165 | 0.8475 | 0.7143 | |
| | | 0.5697 | 4.0 | 220 | 0.7843 | 0.6429 | |
| | | 0.8338 | 5.0 | 275 | 0.7055 | 0.6429 | |
| | | 0.6986 | 6.0 | 330 | 0.7369 | 0.7143 | |
| | | 0.5099 | 7.0 | 385 | 0.6787 | 0.7143 | |
| | | 0.5774 | 8.0 | 440 | 0.6369 | 0.7143 | |
| | | 0.7313 | 9.0 | 495 | 0.6106 | 0.7857 | |
| | | 0.5775 | 10.0 | 550 | 0.6296 | 0.7143 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.48.0.dev0 |
| | - Pytorch 2.2.2 |
| | - Datasets 3.2.0 |
| | - Tokenizers 0.21.0 |
| | |
