---
library_name: peft
language:
- hu
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Tiny Hu Test - Zakryah
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Common Voice 17.0
      type: mozilla-foundation/common_voice_17_0
      config: hu
      split: test
      args: 'config: hu, split: test'
    metrics:
    - type: wer
      value: 113.13022828434707
      name: Wer
---

<!-- 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 Test - Zakryah

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: 1.2430
- Wer: 113.1302

## 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: 8
- seed: 42
- 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      |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.3058        | 0.3299 | 1000 | 1.2987          | 114.1613 |
| 1.3143        | 0.6598 | 2000 | 1.2633          | 112.6243 |
| 1.2969        | 0.9898 | 3000 | 1.2478          | 113.3247 |
| 1.2082        | 1.3197 | 4000 | 1.2430          | 113.1302 |


### Framework versions

- PEFT 0.14.1.dev0
- Transformers 4.50.0.dev0
- Pytorch 2.6.0+cu126
- Datasets 3.3.2
- Tokenizers 0.21.0