---
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
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Small Hu Cleaned
  results: []
---

<!-- 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 Hu - cleaned

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16.1 hu cleaned dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0982
- Wer Ortho: 11.0788
- Wer: 10.2129

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 0.0904        | 1.33  | 200  | 0.1232          | 15.4117   | 14.4286 |
| 0.0316        | 2.66  | 400  | 0.0950          | 11.8467   | 10.9171 |
| 0.0136        | 3.99  | 600  | 0.0950          | 11.3208   | 10.4348 |
| 0.0047        | 5.32  | 800  | 0.0959          | 10.9079   | 10.0424 |
| 0.0029        | 6.64  | 1000 | 0.0982          | 11.0788   | 10.2129 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1