---
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 10h
  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: 22.427374799500978
---

<!-- 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 10h

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: 0.3402
- Wer: 22.4274

## 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: 8
- 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: 50
- training_steps: 1500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 1.0548        | 0.1070 | 100  | 1.0200          | 52.0620 |
| 0.6944        | 0.2139 | 200  | 0.7126          | 39.6222 |
| 0.6024        | 0.3209 | 300  | 0.6052          | 36.0791 |
| 0.4697        | 0.4278 | 400  | 0.5303          | 32.5040 |
| 0.4222        | 0.5348 | 500  | 0.4780          | 30.0766 |
| 0.4075        | 0.6417 | 600  | 0.4458          | 28.4691 |
| 0.374         | 0.7487 | 700  | 0.4151          | 26.9292 |
| 0.3381        | 0.8556 | 800  | 0.3949          | 25.4678 |
| 0.3235        | 0.9626 | 900  | 0.3764          | 24.8904 |
| 0.1861        | 1.0695 | 1000 | 0.3643          | 23.5716 |
| 0.1554        | 1.1765 | 1100 | 0.3608          | 23.4183 |
| 0.1639        | 1.2834 | 1200 | 0.3511          | 23.0298 |
| 0.1453        | 1.3904 | 1300 | 0.3449          | 22.6591 |
| 0.1531        | 1.4973 | 1400 | 0.3419          | 22.4452 |
| 0.1299        | 1.6043 | 1500 | 0.3402          | 22.4274 |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1