--- language: - uz license: apache-2.0 base_model: openai/whisper-small tags: - hf-asr-leaderboard - generated_from_trainer datasets: - mozilla-foundation/common_voice_11_0 model-index: - name: Whisper Small Uz - Makhmud Jumanazarov results: [] --- # Whisper Small Uz - Makhmud Jumanazarov This model is a fine-tuned version of [openai/whisper](https://huggingface.co/openai/whisper) on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set: - Loss: 0.3416 - Wer: 34.9285 ## 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 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - 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 | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.4794 | 0.54 | 1000 | 0.4504 | 42.0722 | | 0.313 | 1.08 | 2000 | 0.3821 | 38.9392 | | 0.2948 | 1.62 | 3000 | 0.3468 | 35.4270 | | 0.249 | 2.16 | 4000 | 0.3416 | 34.9285 | ### Framework versions - Transformers 4.37.0.dev0 - Pytorch 2.1.2+cu121 - Datasets 2.16.1 - Tokenizers 0.15.0