---
language:
- hu
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Large-v2 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 Large-v2 Hu - cleaned

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the Common Voice 16.1 hu cleaned dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0393
- Wer Ortho: 4.1403
- Wer: 3.5518

## 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: 5e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 128
- 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: 50
- training_steps: 600
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 0.0716        | 0.34  | 100  | 0.0690          | 6.5849    | 5.9493 |
| 0.0539        | 0.69  | 200  | 0.0520          | 4.9650    | 4.4825 |
| 0.0381        | 1.03  | 300  | 0.0457          | 4.4900    | 4.0385 |
| 0.0235        | 1.37  | 400  | 0.0423          | 4.2854    | 3.7458 |
| 0.0221        | 1.72  | 500  | 0.0386          | 3.9786    | 3.5518 |
| 0.0158        | 2.06  | 600  | 0.0393          | 4.1403    | 3.6768 |


### Framework versions

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