---
language:
- hu
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Tiny Hu CV17
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 17.0
      type: common_voice_11_0
      config: hu
      split: None
      args: hu
    metrics:
    - name: Wer
      type: wer
      value: 9.925882004150607
---

<!-- 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 Hu CV17

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1387
- Wer Ortho: 10.7883
- Wer: 9.9259

## 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: 7.5e-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
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.6432        | 0.3298 | 250  | 0.7031          | 59.9211   | 57.3051 |
| 0.4839        | 0.6596 | 500  | 0.5256          | 50.4185   | 47.3406 |
| 0.4127        | 0.9894 | 750  | 0.4089          | 40.9250   | 37.8002 |
| 0.2858        | 1.3193 | 1000 | 0.3434          | 34.4725   | 31.8885 |
| 0.2616        | 1.6491 | 1250 | 0.3027          | 32.2956   | 29.2203 |
| 0.2448        | 1.9789 | 1500 | 0.2571          | 28.1705   | 25.3780 |
| 0.1474        | 2.3087 | 1750 | 0.2318          | 25.4426   | 22.8343 |
| 0.1434        | 2.6385 | 2000 | 0.2112          | 22.7749   | 20.3647 |
| 0.14          | 2.9683 | 2250 | 0.1922          | 20.1102   | 17.7883 |
| 0.0768        | 3.2982 | 2500 | 0.1797          | 18.2344   | 15.9917 |
| 0.0764        | 3.6280 | 2750 | 0.1678          | 16.5573   | 14.6161 |
| 0.0737        | 3.9578 | 3000 | 0.1573          | 15.0337   | 13.6199 |
| 0.0375        | 4.2876 | 3250 | 0.1538          | 14.0130   | 12.3243 |
| 0.0357        | 4.6174 | 3500 | 0.1495          | 13.1970   | 11.7106 |
| 0.033         | 4.9472 | 3750 | 0.1435          | 11.9234   | 10.8005 |
| 0.0138        | 5.2770 | 4000 | 0.1422          | 11.8873   | 10.7026 |
| 0.0137        | 5.6069 | 4250 | 0.1398          | 11.4477   | 10.4684 |
| 0.0135        | 5.9367 | 4500 | 0.1381          | 11.1436   | 10.2639 |
| 0.0072        | 6.2665 | 4750 | 0.1388          | 10.7853   | 9.9140  |
| 0.0065        | 6.5963 | 5000 | 0.1387          | 10.7883   | 9.9259  |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1