---
language:
- uz
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Whisper Medium UZ - Bahriddin Mo'minov
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 16.1
      type: mozilla-foundation/common_voice_16_1
      config: uz
      split: test
      args: 'config: uz, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 17.28008879695265
---

<!-- 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 UZ - Bahriddin Mo'minov

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 16.1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2593
- Wer: 17.2801

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer     |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.4581        | 0.2641 | 1000  | 0.3953          | 30.3663 |
| 0.3859        | 0.5282 | 2000  | 0.3257          | 26.6366 |
| 0.2601        | 0.7923 | 3000  | 0.2745          | 22.5373 |
| 0.1724        | 1.0564 | 4000  | 0.2611          | 21.4740 |
| 0.1338        | 1.3205 | 5000  | 0.2526          | 20.7058 |
| 0.1434        | 1.5846 | 6000  | 0.2428          | 19.7434 |
| 0.1136        | 1.8487 | 7000  | 0.2362          | 19.1380 |
| 0.0783        | 2.1128 | 8000  | 0.2387          | 18.7193 |
| 0.0692        | 2.3769 | 9000  | 0.2349          | 18.4846 |
| 0.0722        | 2.6410 | 10000 | 0.2343          | 18.8605 |
| 0.0683        | 2.9051 | 11000 | 0.2297          | 18.0129 |
| 0.0482        | 3.1692 | 12000 | 0.2443          | 18.1920 |
| 0.0231        | 3.4332 | 13000 | 0.2442          | 17.7089 |
| 0.0255        | 3.6973 | 14000 | 0.2468          | 17.7821 |
| 0.022         | 3.9614 | 15000 | 0.2455          | 17.5538 |
| 0.0092        | 4.2255 | 16000 | 0.2553          | 17.5424 |
| 0.0058        | 4.4896 | 17000 | 0.2614          | 17.5828 |
| 0.0048        | 4.7537 | 18000 | 0.2593          | 17.2801 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.2.2+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1