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---
language:
- uz
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Whisper Small Uz - Aslon Khamidov -- with Uzbek Voice dataset
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: 30.20491240338149
---
<!-- 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 Uz - Aslon Khamidov -- with Uzbek Voice dataset
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16.1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3052
- Wer: 30.2049
## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 15000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.4689 | 0.0210 | 1000 | 0.5616 | 48.2462 |
| 0.3234 | 0.0420 | 2000 | 0.4695 | 44.8210 |
| 0.3078 | 0.0630 | 3000 | 0.4184 | 38.8747 |
| 0.2845 | 0.0840 | 4000 | 0.3955 | 36.2861 |
| 0.2771 | 0.1050 | 5000 | 0.3720 | 35.5344 |
| 0.2459 | 0.1260 | 6000 | 0.3649 | 35.9415 |
| 0.2482 | 0.1470 | 7000 | 0.3499 | 34.3993 |
| 0.26 | 0.1680 | 8000 | 0.3389 | 32.9183 |
| 0.2128 | 0.1891 | 9000 | 0.3321 | 33.2493 |
| 0.2092 | 0.2101 | 10000 | 0.3215 | 31.4973 |
| 0.1942 | 0.2311 | 11000 | 0.3194 | 31.0465 |
| 0.1912 | 0.2521 | 12000 | 0.3184 | 31.2850 |
| 0.2199 | 0.2731 | 13000 | 0.3100 | 30.6395 |
| 0.1861 | 0.2941 | 14000 | 0.3059 | 30.8667 |
| 0.2344 | 0.3151 | 15000 | 0.3052 | 30.2049 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.2.0
- Datasets 2.19.2
- Tokenizers 0.19.1
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