---
language:
- hu
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- fsicoli/common_voice_18_0
metrics:
- wer
model-index:
- name: Whisper Small Hu CV18
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: google/flerus
      type: f
      config: hu_hu
      split: train
      args: hu_hu
    metrics:
    - name: Wer
      type: wer
      value: 25.98178929048856
pipeline_tag: automatic-speech-recognition
---

<!-- 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 CV18

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co./openai/whisper-small) on the Common Voice 18.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6647
- Wer Ortho: 32.6950
- Wer: 25.9818

## 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: 2.5e-05
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.2902        | 0.1723 | 250  | 0.6498          | 43.8115   | 38.8390 |
| 0.235         | 0.3446 | 500  | 0.6526          | 43.4572   | 37.5766 |
| 0.1898        | 0.5169 | 750  | 0.6127          | 40.0623   | 34.8072 |
| 0.177         | 0.6892 | 1000 | 0.5866          | 39.0613   | 33.7390 |
| 0.1461        | 0.8615 | 1250 | 0.5848          | 37.2397   | 31.7552 |
| 0.0834        | 1.0338 | 1500 | 0.5942          | 36.6963   | 30.8611 |
| 0.0783        | 1.2061 | 1750 | 0.5973          | 36.2904   | 29.8850 |
| 0.0757        | 1.3784 | 2000 | 0.6127          | 36.8602   | 30.0451 |
| 0.0737        | 1.5507 | 2250 | 0.5925          | 35.8202   | 29.6189 |
| 0.0724        | 1.7229 | 2500 | 0.5721          | 34.6654   | 29.0627 |
| 0.0707        | 1.8952 | 2750 | 0.5818          | 34.6326   | 28.4650 |
| 0.0292        | 2.0675 | 3000 | 0.5917          | 34.4423   | 28.0841 |
| 0.0288        | 2.2398 | 3250 | 0.6147          | 34.3465   | 28.0210 |
| 0.0283        | 2.4121 | 3500 | 0.6279          | 34.7310   | 28.1572 |
| 0.0319        | 2.5844 | 3750 | 0.6122          | 33.9229   | 27.3514 |
| 0.0292        | 2.7567 | 4000 | 0.5988          | 33.6947   | 27.7600 |
| 0.0262        | 2.9290 | 4250 | 0.6170          | 33.8876   | 27.3716 |
| 0.0093        | 3.1013 | 4500 | 0.6297          | 32.9862   | 26.4131 |
| 0.0094        | 3.2736 | 4750 | 0.6167          | 32.2336   | 26.3790 |
| 0.0086        | 3.4459 | 5000 | 0.6430          | 32.9068   | 26.3904 |
| 0.0094        | 3.6182 | 5250 | 0.6432          | 32.9749   | 26.4358 |
| 0.0088        | 3.7905 | 5500 | 0.6330          | 32.8438   | 26.3551 |
| 0.0082        | 3.9628 | 5750 | 0.6530          | 33.4325   | 26.6212 |
| 0.0035        | 4.1351 | 6000 | 0.6549          | 32.8589   | 26.1924 |
| 0.003         | 4.3074 | 6250 | 0.6625          | 32.7757   | 25.9175 |
| 0.003         | 4.4797 | 6500 | 0.6684          | 32.6950   | 25.8393 |
| 0.0032        | 4.6520 | 6750 | 0.6622          | 32.3912   | 25.7687 |
| 0.0027        | 4.8243 | 7000 | 0.6667          | 32.6585   | 25.8847 |
| 0.0028        | 4.9966 | 7250 | 0.6647          | 32.6950   | 25.9818 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.3.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1