metadata
library_name: transformers
language:
- uz
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- uzbekvoice-7k
metrics:
- wer
model-index:
- name: Whisper Small UZ - Link Data
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: UzbekVoice 7K Row
type: uzbekvoice-7k
metrics:
- type: wer
value: 39.64238988225033
name: Wer
Whisper Small UZ - Link Data
This model is a fine-tuned version of openai/whisper-small on the UzbekVoice 7K Row dataset. It achieves the following results on the evaluation set:
- Loss: 0.5898
- Wer: 39.6424
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: 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 |
|---|---|---|---|---|
| 0.2091 | 2.5381 | 1000 | 0.4622 | 44.1343 |
| 0.0232 | 5.0761 | 2000 | 0.4993 | 41.2124 |
| 0.004 | 7.6142 | 3000 | 0.5522 | 39.5988 |
| 0.001 | 10.1523 | 4000 | 0.5789 | 39.2499 |
| 0.0009 | 12.6904 | 5000 | 0.5898 | 39.6424 |
Framework versions
- Transformers 4.57.0
- Pytorch 2.8.0+cu126
- Datasets 4.1.1
- Tokenizers 0.22.1