---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
language:
- hu
widget:
- example_title: Sample 1
  src: https://huggingface.co/datasets/Hungarians/samples/resolve/main/Sample1.flac
- example_title: Sample 2
  src: https://huggingface.co/datasets/Hungarians/samples/resolve/main/Sample2.flac
metrics:
- wer
pipeline_tag: automatic-speech-recognition
model-index:
- name: Whisper Tiny Hungarian
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 16.0 - Hungarian
      type: mozilla-foundation/common_voice_16_0
      config: hu
      split: test
      args: hu
    metrics:
    - name: Wer
      type: wer
      value: 32.2247
      verified: true

---

<!-- 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 Tiny Hungarian

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 16 dataset of Mozilla Foundation.
It achieves the following results on the evaluation set:
- Loss: 0.3628
- Wer Ortho: 34.7985
- Wer: 32.2247


## 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: 3.75e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 0.7288        | 0.17  | 500  | 0.7093          | 59.8298   | 57.4443 |
| 0.5483        | 0.33  | 1000 | 0.5648          | 52.3541   | 49.3122 |
| 0.4647        | 0.5   | 1500 | 0.4912          | 46.1159   | 42.9533 |
| 0.3925        | 0.67  | 2000 | 0.4463          | 42.8674   | 39.9838 |
| 0.3682        | 0.84  | 2500 | 0.4258          | 41.1739   | 38.0487 |
| 0.3219        | 1.0   | 3000 | 0.3932          | 37.5828   | 34.7286 |
| 0.2638        | 1.17  | 3500 | 0.3909          | 37.8060   | 35.0311 |
| 0.2507        | 1.34  | 4000 | 0.3881          | 36.7856   | 34.1199 |
| 0.2483        | 1.51  | 4500 | 0.3737          | 35.5778   | 32.9881 |
| 0.2444        | 1.67  | 5000 | 0.3628          | 34.7985   | 32.2247 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0