transformers tensorboard safetensors whisper audio-classification generated_from_trainer dataset:audiofolder model-index endpoints_compatible region:us
---
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: pd-diagnosis-model-phonation-600
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: audiofolder
      type: audiofolder
      config: default
      split: test+validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8
---

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# pd-diagnosis-model-phonation-600

This model was trained from scratch on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5264
- Accuracy: 0.8

## 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: 4
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.001
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1532        | 1.0   | 127  | 0.5264          | 0.8      |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.1
- Datasets 2.16.1
- Tokenizers 0.15.0
