---
language:
- hu
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Medium HU
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 13
      type: mozilla-foundation/common_voice_13_0
      config: hu
      split: test
      args: hu
    metrics:
    - name: Wer
      type: wer
      value: 14.829034193161366
---

<!-- 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 Medium HU

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 13 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2699
- Wer Ortho: 17.1763
- Wer: 14.8290

## 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: 1e-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: 50
- training_steps: 20000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:-------:|
| 0.0804        | 1.38  | 2000  | 0.1977          | 19.2869   | 16.6612 |
| 0.038         | 2.76  | 4000  | 0.2028          | 18.2211   | 15.7494 |
| 0.014         | 4.14  | 6000  | 0.2190          | 17.9961   | 15.3466 |
| 0.0107        | 5.51  | 8000  | 0.2328          | 17.3490   | 14.9370 |
| 0.0144        | 6.89  | 10000 | 0.2376          | 17.4153   | 14.9559 |
| 0.0049        | 8.27  | 12000 | 0.2424          | 16.9984   | 14.6953 |
| 0.0071        | 9.65  | 14000 | 0.2594          | 17.6961   | 15.3586 |
| 0.0037        | 11.03 | 16000 | 0.2546          | 17.2007   | 14.8667 |
| 0.0078        | 12.41 | 18000 | 0.2644          | 17.5757   | 15.1495 |
| 0.0043        | 13.78 | 20000 | 0.2699          | 17.1763   | 14.8290 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.17.0
- Tokenizers 0.15.2