---
license: apache-2.0
base_model: openai/whisper-small
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 Small 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: 18.8314
      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 Small Hungarian (training in progress)

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

Tempolary at step 3500: 

- Wer: 18.8314

Unfortunatly the colab disconected, this is the end... :( maybe later continue


## 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: 1.25e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 400
- planed training_steps: 6000
- executed steps: 3500 only (colab dc)
- mixed_precision_training: Native AMP

### Training results

| Steps | Training Loss | Validation Loss | Wer Ortho |    Wer    |
|:-----:|:-------------:|:---------------:|:---------:|:---------:|
| 500	|   0.354600    |    0.349688     |	34.385555 |	31.246555 |
| 1000	|   0.283800	|    0.290485	  | 29.696507 |	26.625776 |
| 1500	|   0.248800	|    0.255122	  | 26.360826 |	23.300925 |
| 2000	|   0.198300	|    0.234539	  | 24.557530 |	21.714145 |
| 2500	|   0.196300    |    0.224310	  | 23.557423 |	20.698512 |
| 3000	|   0.153000	|    0.210894	  | 22.088291 |	19.231356 |
| 3500	|   0.109100	|    0.210817	  | 21.465313 |	18.831435 |

### Framework versions

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