---
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: 24.555998550199348
---

<!-- 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: 0.4242
- Wer: 24.5560

## 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: 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     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.3363        | 2.02  | 500   | 0.3762          | 29.7934 |
| 0.0945        | 5.02  | 1000  | 0.3418          | 27.6912 |
| 0.0332        | 8.01  | 1500  | 0.3353          | 26.1689 |
| 0.0147        | 11.01 | 2000  | 0.3476          | 26.1327 |
| 0.0071        | 14.01 | 2500  | 0.3623          | 25.9333 |
| 0.0034        | 17.01 | 3000  | 0.3789          | 25.2084 |
| 0.0024        | 20.01 | 3500  | 0.3827          | 24.8641 |
| 0.0026        | 23.01 | 4000  | 0.3877          | 25.3171 |
| 0.0021        | 26.01 | 4500  | 0.3933          | 25.4259 |
| 0.0014        | 29.01 | 5000  | 0.3941          | 25.0997 |
| 0.0008        | 32.01 | 5500  | 0.4014          | 25.0997 |
| 0.0004        | 35.01 | 6000  | 0.4035          | 24.8278 |
| 0.0003        | 38.01 | 6500  | 0.4080          | 24.9184 |
| 0.0003        | 41.01 | 7000  | 0.4120          | 24.8097 |
| 0.0002        | 44.01 | 7500  | 0.4151          | 24.6104 |
| 0.0002        | 47.01 | 8000  | 0.4176          | 24.3929 |
| 0.0002        | 50.01 | 8500  | 0.4200          | 24.5198 |
| 0.0001        | 53.0  | 9000  | 0.4230          | 24.5198 |
| 0.0001        | 56.0  | 9500  | 0.4252          | 24.4291 |
| 0.0001        | 59.0  | 10000 | 0.4242          | 24.5560 |


### Framework versions

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