metadata
language:
- uk
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Whisper Small Ukrainian
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 16.1
type: mozilla-foundation/common_voice_16_1
config: uk
split: None
args: 'config: uk, split: test'
metrics:
- name: Wer
type: wer
value: 26.357029928161317
Whisper Small Ukrainian
This model is a fine-tuned version of openai/whisper-small on the Common Voice 16.1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2744
- Wer: 26.3570
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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.278 | 0.47 | 1000 | 0.3330 | 31.8004 |
| 0.2662 | 0.94 | 2000 | 0.2961 | 29.4969 |
| 0.1403 | 1.42 | 3000 | 0.2796 | 27.3209 |
| 0.1105 | 1.89 | 4000 | 0.2702 | 26.2724 |
| 0.0719 | 2.36 | 5000 | 0.2744 | 26.3570 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.2.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2