---
library_name: transformers
language:
- uz
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Medium Uzbek
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 17.0
      type: mozilla-foundation/common_voice_17_0
      config: uz
      split: None
      args: 'config: uz, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 38.19985168705969
---

<!-- 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 Medium Uzbek

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4148
- Wer: 38.1999

## 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: 3e-05
- train_batch_size: 64
- eval_batch_size: 16
- 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: 200
- training_steps: 1500

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.6553        | 0.5330 | 250  | 0.5830          | 51.2637 |
| 0.3945        | 1.0661 | 500  | 0.4612          | 41.6914 |
| 0.3352        | 1.5991 | 750  | 0.4360          | 42.0931 |
| 0.2028        | 2.1322 | 1000 | 0.4155          | 38.1133 |
| 0.1956        | 2.6652 | 1250 | 0.4081          | 37.6900 |
| 0.1202        | 3.1983 | 1500 | 0.4148          | 38.1999 |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0