---
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: 64.62662626982713
---

<!-- 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: 1.6643
- Wer: 64.6266

## 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: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 2.0562        | 6.6667  | 100  | 2.2740          | 83.4860 |
| 0.9187        | 13.3333 | 200  | 1.7749          | 76.7385 |
| 0.4133        | 20.0    | 300  | 1.6576          | 69.3317 |
| 0.1671        | 26.6667 | 400  | 1.6334          | 67.2679 |
| 0.0603        | 33.3333 | 500  | 1.6319          | 66.2770 |
| 0.0245        | 40.0    | 600  | 1.6433          | 65.6496 |
| 0.0138        | 46.6667 | 700  | 1.6522          | 64.6730 |
| 0.0104        | 53.3333 | 800  | 1.6591          | 64.5019 |
| 0.0089        | 60.0    | 900  | 1.6632          | 64.4876 |
| 0.0083        | 66.6667 | 1000 | 1.6643          | 64.6266 |


### Framework versions

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