metadata
language:
- uz
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- audio
- automatic-speech-recognition
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Tiny Uzbek
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_13_0
type: mozilla-foundation/common_voice_13_0
config: uz
split: test
args: uz
metrics:
- name: Wer
type: wer
value: 36.79056163528213
pipeline_tag: automatic-speech-recognition
Whisper Tiny Uzbek
This model is a fine-tuned version of openai/whisper-tiny on the mozilla-foundation/common_voice_13_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2981
- Wer Ortho: 47.7812
- Wer: 36.7906
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 50
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.2929 | 0.8 | 3000 | 0.3281 | 50.8851 | 40.4395 |
| 0.2194 | 1.59 | 6000 | 0.3110 | 49.2325 | 37.9320 |
| 0.177 | 2.39 | 9000 | 0.3003 | 47.8700 | 36.8366 |
| 0.1574 | 3.18 | 12000 | 0.2997 | 48.2291 | 37.0491 |
| 0.1524 | 3.98 | 15000 | 0.2958 | 47.2395 | 36.4400 |
| 0.1455 | 4.77 | 18000 | 0.2981 | 47.7812 | 36.7906 |
Framework versions
- Transformers 4.35.1
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1