---
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 1h
  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: 47.79183746212796
---

<!-- 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 1h

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: 0.9900
- Wer: 47.7918

## 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: 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: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 2.4073        | 1.1236  | 100  | 2.2555          | 82.9549 |
| 1.5143        | 2.2472  | 200  | 1.6651          | 73.4557 |
| 1.1865        | 3.3708  | 300  | 1.4237          | 65.1256 |
| 0.9368        | 4.4944  | 400  | 1.2874          | 59.4832 |
| 0.8009        | 5.6180  | 500  | 1.1957          | 56.5461 |
| 0.6722        | 6.7416  | 600  | 1.1345          | 54.6890 |
| 0.5726        | 7.8652  | 700  | 1.0894          | 53.1919 |
| 0.5068        | 8.9888  | 800  | 1.0575          | 51.7769 |
| 0.4239        | 10.1124 | 900  | 1.0351          | 50.8002 |
| 0.3799        | 11.2360 | 1000 | 1.0197          | 49.9198 |
| 0.295         | 12.3596 | 1100 | 1.0110          | 49.3673 |
| 0.2852        | 13.4831 | 1200 | 1.0022          | 48.7507 |
| 0.2478        | 14.6067 | 1300 | 0.9965          | 48.3800 |
| 0.2267        | 15.7303 | 1400 | 0.9931          | 48.1911 |
| 0.1986        | 16.8539 | 1500 | 0.9916          | 48.1412 |
| 0.1922        | 17.9775 | 1600 | 0.9907          | 47.9558 |
| 0.1724        | 19.1011 | 1700 | 0.9905          | 47.8703 |
| 0.1709        | 20.2247 | 1800 | 0.9900          | 47.9059 |
| 0.1749        | 21.3483 | 1900 | 0.9900          | 47.7598 |
| 0.145         | 22.4719 | 2000 | 0.9900          | 47.7918 |


### Framework versions

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