metadata
library_name: transformers
language:
- uz
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Small uz - Yorkerdev
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_17_0
config: uz
split: test
args: 'config: uz, split: test'
metrics:
- name: Wer
type: wer
value: 33.687376750455556
Whisper Small uz - Yorkerdev
This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3481
- Wer: 33.6874
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use adamw_torch 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: 8000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.6132 | 0.2640 | 1000 | 0.5668 | 49.3073 |
| 0.4946 | 0.5280 | 2000 | 0.4544 | 40.9201 |
| 0.4363 | 0.7919 | 3000 | 0.4098 | 37.8935 |
| 0.3124 | 1.0557 | 4000 | 0.3872 | 38.4938 |
| 0.2919 | 1.3197 | 5000 | 0.3674 | 35.4522 |
| 0.2711 | 1.5837 | 6000 | 0.3577 | 34.6721 |
| 0.2754 | 1.8476 | 7000 | 0.3491 | 33.6874 |
| 0.2024 | 2.1114 | 8000 | 0.3481 | 33.6874 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu118
- Datasets 3.3.2
- Tokenizers 0.21.0