metadata
language:
- ru
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Ru - v3
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: ru
split: test
args: 'config: ru, split: test'
metrics:
- name: Wer
type: wer
value: 15.209534043176712
Whisper Small Ru - v3
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2266
- Wer: 15.2095
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: 32
- 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1682 | 0.9843 | 1000 | 0.2050 | 16.5356 |
| 0.0903 | 1.9685 | 2000 | 0.1953 | 15.6760 |
| 0.0417 | 2.9528 | 3000 | 0.2006 | 15.3500 |
| 0.0175 | 3.9370 | 4000 | 0.2144 | 15.1534 |
| 0.0093 | 4.9213 | 5000 | 0.2266 | 15.2095 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1