---
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- data/copas
metrics:
- wer
model-index:
- name: Whisper Small dysarthric Dutch
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: data/copas copas-full
      type: data/copas
      config: copas-full
      split: test
      args: copas-full
    metrics:
    - name: Wer
      type: wer
      value: 22.87060529177238
---

<!-- 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 dysarthric Dutch

This model is a fine-tuned version of [qmeeus/whisper-small-nl](https://huggingface.co/qmeeus/whisper-small-nl) on the data/copas copas-full dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4891
- Wer: 22.8706

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.1493        | 2.02  | 500   | 0.3960          | 28.9779 |
| 0.0383        | 5.02  | 1000  | 0.4041          | 26.5132 |
| 0.0264        | 8.01  | 1500  | 0.4274          | 25.5890 |
| 0.0155        | 11.01 | 2000  | 0.4437          | 24.7735 |
| 0.0041        | 14.01 | 2500  | 0.4454          | 25.0453 |
| 0.0044        | 17.01 | 3000  | 0.4444          | 23.9761 |
| 0.0044        | 20.01 | 3500  | 0.4394          | 23.4868 |
| 0.0022        | 23.01 | 4000  | 0.4415          | 22.8525 |
| 0.0034        | 26.01 | 4500  | 0.4602          | 23.6499 |
| 0.0027        | 29.01 | 5000  | 0.4577          | 23.3780 |
| 0.0072        | 32.01 | 5500  | 0.4573          | 23.3962 |
| 0.0002        | 35.01 | 6000  | 0.4673          | 23.1062 |
| 0.0001        | 38.01 | 6500  | 0.4723          | 22.9975 |
| 0.0001        | 41.01 | 7000  | 0.4770          | 23.0881 |
| 0.0           | 44.01 | 7500  | 0.4807          | 23.0518 |
| 0.0           | 47.01 | 8000  | 0.4835          | 22.9612 |
| 0.0           | 50.01 | 8500  | 0.4857          | 22.9250 |
| 0.0           | 53.0  | 9000  | 0.4874          | 22.9069 |
| 0.0           | 56.0  | 9500  | 0.4887          | 22.9069 |
| 0.0           | 59.0  | 10000 | 0.4891          | 22.8706 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.12.1