metadata
language:
- uz
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Whisper Large v3 Turbo - Bahriddin Muminov
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: 25.073985739794963
Whisper Large v3 Turbo - Bahriddin Muminov
This model is a fine-tuned version of openai/whisper-large-v3-turbo on the Common Voice 16.1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2643
- Wer: 25.0740
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: 1000
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3109 | 0.04 | 2000 | 0.4220 | 36.8942 |
| 0.2529 | 0.07 | 4000 | 0.3593 | 31.0915 |
| 0.2123 | 0.11 | 6000 | 0.3150 | 28.2694 |
| 0.1936 | 0.14 | 8000 | 0.2773 | 27.4353 |
| 0.1716 | 0.18 | 10000 | 0.2643 | 25.0740 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2