---
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: whisper_base_finetuned
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: audiofolder
      type: audiofolder
      config: default
      split: validation
      args: default
    metrics:
    - name: Wer
      type: wer
      value: 0.3192600084831479
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/querying/huggingface/runs/1wtpwccg)
# whisper_base_finetuned

This model was trained from scratch on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3375
- Wer: 0.3193

## 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
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 64
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.4111        | 1.0   | 973  | 0.4590          | 0.4551 |
| 0.4068        | 2.0   | 1946 | 0.3847          | 0.4812 |
| 0.3617        | 3.0   | 2919 | 0.3585          | 0.4326 |
| 0.3144        | 4.0   | 3892 | 0.3436          | 0.3594 |
| 0.272         | 5.0   | 4865 | 0.3425          | 0.3639 |
| 0.2246        | 6.0   | 5838 | 0.3371          | 0.3341 |
| 0.1541        | 7.0   | 6811 | 0.3404          | 0.3377 |
| 0.1387        | 8.0   | 7784 | 0.3370          | 0.3196 |
| 0.1554        | 9.0   | 8757 | 0.3387          | 0.3113 |
| 0.1692        | 10.0  | 9730 | 0.3375          | 0.3193 |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.2.1
- Datasets 2.19.0
- Tokenizers 0.19.1