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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 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 |