---
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
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Medium Hu Cleaned
  results: []
---

<!-- 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 - cleaned

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 16.1 hu cleaned dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0486
- Wer Ortho: 5.5028
- Wer: 4.9758

## 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: 6.25e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 0.0708        | 0.69  | 200  | 0.0712          | 8.0529    | 7.4029 |
| 0.0279        | 1.37  | 400  | 0.0554          | 6.4034    | 5.8342 |
| 0.0138        | 2.06  | 600  | 0.0487          | 5.6875    | 5.1732 |
| 0.0077        | 2.75  | 800  | 0.0479          | 5.4467    | 4.8837 |
| 0.0037        | 3.43  | 1000 | 0.0486          | 5.5028    | 4.9758 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1