---
library_name: transformers
language:
- uk
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Small UK - Bohdan's Fine-Tune
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Google FLEURS (Ukrainian)
      type: google/fleurs
      config: uk_ua
      split: None
      args: 'config: uk_ua, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 17.213578500707214
---

<!-- 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 Small UK - Bohdan's Fine-Tune

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Google FLEURS (Ukrainian) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3156
- Wer: 17.2136

## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.007         | 5.1020  | 1000 | 0.2776          | 17.6874 |
| 0.0009        | 10.2041 | 2000 | 0.2952          | 17.1358 |
| 0.0005        | 15.3061 | 3000 | 0.3098          | 17.1216 |
| 0.0004        | 20.4082 | 4000 | 0.3156          | 17.2136 |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.8.0+cu128
- Datasets 2.21.0
- Tokenizers 0.22.1