metadata
language:
- ru
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Small Ru - Model_ru_3
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 13
type: mozilla-foundation/common_voice_13_0
config: ru
split: test
args: ru
metrics:
- name: Wer
type: wer
value: 13.30140186915888
Whisper Small Ru - Model_ru_3
This model is a fine-tuned version of openai/whisper-small on the Common Voice 13 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2080
- Wer Ortho: 17.4462
- Wer: 13.3014
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: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.2085 | 0.22 | 500 | 0.2366 | 19.9234 | 14.9498 |
| 0.1875 | 0.44 | 1000 | 0.2176 | 19.3079 | 14.5643 |
| 0.1688 | 0.66 | 1500 | 0.2095 | 18.3736 | 13.9287 |
| 0.1678 | 0.88 | 2000 | 0.2038 | 17.7325 | 13.4381 |
| 0.0853 | 1.1 | 2500 | 0.2036 | 17.0309 | 12.7488 |
| 0.0822 | 1.32 | 3000 | 0.2046 | 17.6894 | 13.2780 |
| 0.0775 | 1.54 | 3500 | 0.2051 | 16.9948 | 12.7126 |
| 0.0727 | 1.76 | 4000 | 0.2080 | 17.4462 | 13.3014 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.3.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2