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---
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
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