---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_6_1
metrics:
- wer
model-index:
- name: Whisper Small Frisian 10m
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 6.1
      type: mozilla-foundation/common_voice_6_1
      args: 'config: frisian, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 72.75540681564648
---

<!-- 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 Frisian 10m

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 6.1 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6189
- Wer: 72.7554

## 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-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 2.2806        | 25.0  | 200  | 2.4315          | 86.9013 |
| 0.5256        | 50.0  | 400  | 1.6206          | 77.5451 |
| 0.0145        | 75.0  | 600  | 1.5883          | 73.7378 |
| 0.0055        | 100.0 | 800  | 1.6120          | 72.8274 |
| 0.0044        | 125.0 | 1000 | 1.6189          | 72.7554 |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1