metadata
library_name: transformers
language:
- kk
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 KK - Kazakh Augmented
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_17_0
config: kk
split: test
args: 'config: kk, split: test'
metrics:
- name: Wer
type: wer
value: 46.55716993051169
Whisper Small KK - Kazakh Augmented
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: 0.6225
- Wer: 46.5572
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 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: 100
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1921 | 1.5152 | 100 | 0.5052 | 47.7890 |
| 0.0705 | 3.0303 | 200 | 0.5226 | 49.1156 |
| 0.0077 | 4.5455 | 300 | 0.5783 | 47.1573 |
| 0.0035 | 6.0606 | 400 | 0.5758 | 46.0834 |
| 0.0008 | 7.5758 | 500 | 0.6011 | 46.4940 |
| 0.0006 | 9.0909 | 600 | 0.6126 | 46.3677 |
| 0.0003 | 10.6061 | 700 | 0.6159 | 44.4409 |
| 0.0002 | 12.1212 | 800 | 0.6194 | 44.3146 |
| 0.0002 | 13.6364 | 900 | 0.6216 | 46.5256 |
| 0.0002 | 15.1515 | 1000 | 0.6225 | 46.5572 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu118
- Datasets 3.3.2
- Tokenizers 0.21.0