--- language: - ml license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - google/fleurs metrics: - wer model-index: - name: Whisper Small Malayalam - Arjun Shaji results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: google/fleurs type: google/fleurs config: ml_in split: None args: 'config: ml, split: test' metrics: - name: Wer type: wer value: 52.33970351848545 --- # Whisper Small Malayalam - Arjun Shaji This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the google/fleurs dataset. It achieves the following results on the evaluation set: - Loss: 0.1677 - Wer: 52.3397 ## 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 | |:-------------:|:-------:|:----:|:---------------:|:-------:| | 0.0239 | 5.1020 | 1000 | 0.1136 | 54.3847 | | 0.002 | 10.2041 | 2000 | 0.1426 | 52.9827 | | 0.0003 | 15.3061 | 3000 | 0.1584 | 52.5808 | | 0.0001 | 20.4082 | 4000 | 0.1643 | 52.3129 | | 0.0001 | 25.5102 | 5000 | 0.1677 | 52.3397 | ### Framework versions - Transformers 4.41.0 - Pytorch 2.3.0+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1