---
library_name: transformers
language:
- uk
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper tiny uk - Herai Hench KI-11
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: uk
      split: None
      args: 'config: uk, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 58.393189678105884
---

<!-- 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 uk - Herai Hench KI-11

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7245
- Wer: 58.3932
- Cer: 18.1853

## 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: 6e-06
- 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: 6000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     | Cer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|
| 0.7374        | 0.8065 | 1000 | 0.8454          | 64.6981 | 22.8643 |
| 0.6193        | 1.6129 | 2000 | 0.7735          | 61.6387 | 20.3717 |
| 0.5334        | 2.4194 | 3000 | 0.7444          | 60.3618 | 18.8322 |
| 0.4709        | 3.2258 | 4000 | 0.7318          | 59.5903 | 19.9146 |
| 0.4616        | 4.0323 | 5000 | 0.7242          | 58.3134 | 18.0517 |
| 0.4209        | 4.8387 | 6000 | 0.7245          | 58.3932 | 18.1853 |


### Framework versions

- Transformers 4.52.4
- Pytorch 2.5.1+cu124
- Datasets 3.6.0
- Tokenizers 0.21.0