--- language: - hi base_model: nurzhanit/whisper-enhanced-ml tags: - hf-asr-leaderboard - generated_from_trainer datasets: - mozilla-foundation/common_voice_11_0 metrics: - wer model-index: - name: Whisper Small Hi - Sanchit Gandhi results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 11.0 type: mozilla-foundation/common_voice_11_0 config: default split: None args: 'config: hi, split: test' metrics: - name: Wer type: wer value: 0.05155525004296271 --- # Whisper Small Hi - Sanchit Gandhi This model is a fine-tuned version of [nurzhanit/whisper-enhanced-ml](https://huggingface.co/nurzhanit/whisper-enhanced-ml) on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set: - Loss: 0.0005 - Wer: 0.0516 ## 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: 25 - training_steps: 500 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:------:| | 0.0929 | 1.0 | 50 | 0.0404 | 8.1114 | | 0.0385 | 2.0 | 100 | 0.0161 | 3.0761 | | 0.0176 | 3.0 | 150 | 0.0081 | 1.4779 | | 0.0087 | 4.0 | 200 | 0.0034 | 0.6358 | | 0.0038 | 5.0 | 250 | 0.0020 | 0.4296 | | 0.0025 | 6.0 | 300 | 0.0011 | 0.1203 | | 0.0017 | 7.0 | 350 | 0.0008 | 0.0516 | | 0.0009 | 8.0 | 400 | 0.0006 | 0.0516 | | 0.0007 | 9.0 | 450 | 0.0006 | 0.0516 | | 0.0007 | 10.0 | 500 | 0.0005 | 0.0516 | ### Framework versions - Transformers 4.40.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.2 - Tokenizers 0.19.1