Jb Whisper Parkinson Model
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set: Loss: 0.3598 Accuracy: 1.0 F1 Macro: 1.0
Fuente del modelo
- Tipo
- Other
- Tamaño del archivo
- 337 MB
- Modelo base
- openai/whisper-small
- Versión
- vRevision 49e807e
- Actualizado
- 31 oct 2026
- Descargas
- 6
- Fuente
- Hugging Face
Descripción de la fuente
jb_whisper_parkinson_model
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3598
- Accuracy: 1.0
- F1 Macro: 1.0
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
|---|---|---|---|---|---|
| 0.5351 | 1.0 | 70 | 0.3526 | 1.0 | 1.0 |
| 0.5046 | 2.0 | 140 | 0.2548 | 1.0 | 1.0 |
| 0.4078 | 3.0 | 210 | 0.2285 | 1.0 | 1.0 |
| 0.4748 | 4.0 | 280 | 0.2205 | 1.0 | 1.0 |
| 0.5464 | 5.0 | 350 | 0.2163 | 1.0 | 1.0 |
Framework versions
- Transformers 4.57.6
- Pytorch 2.11.0+cu130
- Datasets 4.8.4
- Tokenizers 0.22.2
Fuentes
1 fuente
Fuentes
1 fuenteVerificado 31 oct
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Artefactos del modelo
1 artefacto
Artefactos del modelo
1 artefactomodel.safetensors
safetensors · FP32 (unverified) · 337 MB · SHA-256 6dc86914fc34…d0e4 · Hugging Face
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Extractos de fuentes
3 extractos--- library_name: transformers license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer metrics: - accuracy model-index: - name: jb_whisper_parkinson_model 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. --> # jb_whisper_parkinson_model This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.3598 - Accuracy: 1.0 - F1 Macro: 1.0 ## 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: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 5 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:| | 0.5351 | 1.0 | 70 | 0.3526 | 1.0 | 1.0 | | 0.5046 | 2.0 | 140 | 0.2548 | 1.0 | 1.0 | | 0.4078 | 3.0 | 210 | 0.2285 | 1.0 | 1.0 | | 0.4748 | 4.0 | 280 | 0.2205 | 1.0 | 1.0 | | 0.5464 | 5.0 | 350 | 0.2163 | 1.0 | 1.0 | ### Framework versions - Transformers 4.57.6 - Pytorch 2.11.0+cu130 - Datasets 4.8.4 - Tokenizers 0.22.2
Source context: 6 downloads · 0 likes · Pipeline audio-classification · Library transformers · Repo jakub-02/jb_whisper_parkinson_model
Source context: 5 downloads · 0 likes · Pipeline audio-classification · Library transformers · Repo jakub-02/jb_whisper_parkinson_model
