---
language:
- fy
base_model: distil-small.en
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_6_1
metrics:
- wer
model-index:
- name: DistilFT-Frisian-10h
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_6_fy_NL
      type: mozilla-foundation/common_voice_6_1
      args: 'config: fy-NL, split: train-10h'
    metrics:
    - name: Wer
      type: wer
      value: 26.911423988593835
---

<!-- 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. -->

# DistilFT-Frisian-10h

This model is a fine-tuned version of [distil-small.en](https://huggingface.co./distil-small.en) on the mozilla-foundation/common_voice_6_fy_NL dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5755
- Wer: 26.9114

## 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: 0.0001
- 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: 300
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.9504        | 0.5348 | 500  | 1.0939          | 57.4122 |
| 0.4656        | 1.0695 | 1000 | 0.8241          | 45.7316 |
| 0.4533        | 1.6043 | 1500 | 0.7285          | 41.3474 |
| 0.1745        | 2.1390 | 2000 | 0.6875          | 37.7009 |
| 0.1701        | 2.6738 | 2500 | 0.6261          | 34.7603 |
| 0.0709        | 3.2086 | 3000 | 0.6566          | 33.4415 |
| 0.0731        | 3.7433 | 3500 | 0.5880          | 30.5650 |
| 0.0234        | 4.2781 | 4000 | 0.5949          | 28.8754 |
| 0.0192        | 4.8128 | 4500 | 0.5799          | 27.7063 |
| 0.0038        | 5.3476 | 5000 | 0.5755          | 26.9114 |


### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1