--- language: - uz license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - mozilla-foundation/common_voice_16_1 metrics: - wer model-index: - name: Whisper Small UZ - Bahriddin Mo'minov results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 16.1 type: mozilla-foundation/common_voice_16_1 config: uz split: test args: 'config: uz, split: test' metrics: - name: Wer type: wer value: 28.692515325042255 --- # Whisper Small UZ - Bahriddin Mo'minov This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16.1 dataset. It achieves the following results on the evaluation set: - Loss: 0.3379 - Wer: 28.6925 ## 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 | |:-------------:|:------:|:----:|:---------------:|:-------:| | 0.5499 | 0.2641 | 1000 | 0.5142 | 39.8375 | | 0.4419 | 0.5281 | 2000 | 0.4080 | 33.3644 | | 0.3506 | 0.7922 | 3000 | 0.3544 | 29.7293 | | 0.242 | 1.0562 | 4000 | 0.3379 | 28.6925 | ### Framework versions - Transformers 4.41.0 - Pytorch 2.2.2+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1