metadata
language:
- kk
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Large v3 Kazakh
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: 188.06064434617815
Whisper Large v3 Kazakh
This model is a fine-tuned version of openai/whisper-large-v3 on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5842
- Wer: 188.0606
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0003 | 28.5714 | 1000 | 0.4718 | 546.6835 |
| 0.0 | 57.1429 | 2000 | 0.5506 | 175.4264 |
| 0.0 | 85.7143 | 3000 | 0.5751 | 185.3759 |
| 0.0 | 114.2857 | 4000 | 0.5842 | 188.0606 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 1.12.0
- Datasets 2.20.0
- Tokenizers 0.19.1