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---
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 |