--- language: - hi license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - mozilla-foundation/common_voice_17_0 metrics: - wer model-index: - name: Whisper Small Hi -MUKUND results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 11.0 type: mozilla-foundation/common_voice_17_0 config: te split: None args: 'config: hi, split: test' metrics: - name: Wer type: wer value: 87.36263736263736 --- # Whisper Small Hi -MUKUND This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set: - Loss: 1.0257 - Wer: 87.3626 ## 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 | |:-------------:|:--------:|:----:|:---------------:|:-------:| | 0.0 | 142.8571 | 1000 | 0.7698 | 86.8132 | | 0.0 | 285.7143 | 2000 | 0.8781 | 87.9121 | | 0.0 | 428.5714 | 3000 | 0.9771 | 87.3626 | | 0.0 | 571.4286 | 4000 | 1.0257 | 87.3626 | ### Framework versions - Transformers 4.40.1 - Pytorch 2.2.1+cu121 - Datasets 2.19.0 - Tokenizers 0.19.1