---
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: 25.08155128669808
---

<!-- 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: 0.3314
- Wer: 25.0816

## 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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3462        | 0.1   | 500  | 0.3721          | 29.9746 |
| 0.1205        | 1.1   | 1000 | 0.3286          | 26.4226 |
| 0.0642        | 2.1   | 1500 | 0.3139          | 25.2628 |
| 0.0443        | 3.1   | 2000 | 0.3169          | 25.0453 |
| 0.0356        | 4.1   | 2500 | 0.3226          | 25.0634 |
| 0.0321        | 5.09  | 3000 | 0.3237          | 24.7191 |
| 0.0317        | 6.09  | 3500 | 0.3322          | 24.7735 |
| 0.0347        | 7.09  | 4000 | 0.3355          | 25.0634 |
| 0.0357        | 8.09  | 4500 | 0.3364          | 25.2265 |
| 0.0318        | 9.09  | 5000 | 0.3314          | 25.0816 |


### Framework versions

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