metadata
library_name: transformers
language:
- uz
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- tashkent-dialects-large-v3
metrics:
- wer
model-index:
- name: Whisper large-v3 UZ - Link Data
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Tashkent Dialects large-v3
type: tashkent-dialects-large-v3
metrics:
- type: wer
value: 34.26096387949366
name: Wer
Whisper large-v3 UZ - Link Data
This model is a fine-tuned version of openai/whisper-large-v3 on the Tashkent Dialects large-v3 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4566
- Wer: 34.2610
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.306 | 1.2212 | 1000 | 0.3767 | 37.0396 |
| 0.1833 | 2.4424 | 2000 | 0.3431 | 34.0597 |
| 0.1262 | 3.6636 | 3000 | 0.3548 | 33.7957 |
| 0.0755 | 4.8848 | 4000 | 0.3905 | 34.0269 |
| 0.0284 | 6.1051 | 5000 | 0.4566 | 34.2610 |
Framework versions
- Transformers 4.57.0
- Pytorch 2.8.0+cu126
- Datasets 4.1.1
- Tokenizers 0.22.1