---
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- data/copas
metrics:
- wer
model-index:
- name: Whisper Small 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: 0.0
---

<!-- 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 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: 0.0015
- Wer: 0.0

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1291        | 2.03  | 500  | 0.2953          | 25.0681 |
| 0.0524        | 5.03  | 1000 | 0.1626          | 13.9118 |
| 0.0403        | 8.03  | 1500 | 0.0825          | 6.5450  |
| 0.0349        | 11.03 | 2000 | 0.0409          | 2.5652  |
| 0.0122        | 14.03 | 2500 | 0.0173          | 0.6619  |
| 0.0053        | 17.03 | 3000 | 0.0068          | 0.0822  |
| 0.0032        | 20.02 | 3500 | 0.0037          | 0.0173  |
| 0.0022        | 23.02 | 4000 | 0.0024          | 0.0     |
| 0.0018        | 26.02 | 4500 | 0.0018          | 0.0     |
| 0.0016        | 29.02 | 5000 | 0.0015          | 0.0     |


### Framework versions

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