---
library_name: transformers
language:
- hu
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: pici - Zakryah
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 13.0
      type: mozilla-foundation/common_voice_13_0
      config: hu
      split: None
      args: 'config: hu, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 49.51769610493816
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# pici - Zakryah

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 13.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5618
- Wer: 49.5177

## 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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.7211        | 0.6895 | 1000 | 0.7369          | 59.2806 |
| 0.5253        | 1.3786 | 2000 | 0.6201          | 53.7320 |
| 0.4235        | 2.0676 | 3000 | 0.5741          | 50.7056 |
| 0.4075        | 2.7571 | 4000 | 0.5618          | 49.5177 |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0