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---
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 11000:
- Wer: 8.4969
Unfortunatly the colab disconected, this is the end... :( maybe later continue
My own hungarian language specific compare test result (on CV11):
| Modell | WER | CER | NORMALISED WER | NORMALISED CER |
|:----------------------------------:|:-------------:|:---------------:|:--------------:|:--------------:|
| openai/whisper-tiny | 112.1 | 51.33 | 108.79 | 49.64 |
| openai/whisper-base | 95.87 | 42.84 | 95.68 | 41.38 |
| openai/whisper-small | 53.65 | 15.89 | 49.8 | 14.63 |
| Hungarians/whisper-tiny-cv16-hu | 30.57 | 8.52 | 27.71 | 7.86 |
| Hungarians/whisper-tiny-cv16-hu-v2 | 16.99 | 4.98 | 15.27 | 4.49 |
| Hungarians/whisper-base-cv16-hu | 15.55 | 4.07 | 13.68 | 3.67 |
| Hungarians/whisper-base-cv16-hu-v2 | 12.63 | 3.55 | 11.39 | 3.26 |
| Hungarians/whisper-small-cv16-hu | 17.86 | 4.1 | 15.27 | 3.58 |
| sarpba/whisper-small-cv16-v1.5-hu| 9.94 | 2.41 | 8.50 | 2.14 |
## 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: 15000
- executed steps: 11000 only (colab dc)
- mixed_precision_training: Native AMP
### Training results
| Steps | Training Loss | Validation Loss | Wer Ortho | Wer |
|:-----:|:-------------:|:---------------:|:---------:|:---------:|
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0 |