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---
library_name: transformers
language:
- nl
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- procit009/nl_stt
metrics:
- wer
model-index:
- name: 'Whisper Small nl '
  results: []
---

<!-- 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 nl 

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the procit009/nl_stt dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2637
- Wer: 14.1492

## 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: 5
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2302        | 1.0   | 125  | 0.2444          | 14.2023 |
| 0.1247        | 2.0   | 250  | 0.2396          | 14.4464 |
| 0.036         | 3.0   | 375  | 0.2448          | 13.9582 |
| 0.0117        | 4.0   | 500  | 0.2549          | 14.0113 |
| 0.0049        | 5.0   | 625  | 0.2604          | 15.5928 |
| 0.0031        | 6.0   | 750  | 0.2637          | 14.1492 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0