--- language: - hi license: apache-2.0 base_model: openai/whisper-small tags: - hf-asr-leaderboard - generated_from_trainer datasets: - mozilla-foundation/common_voice_11_0 metrics: - wer model-index: - name: Whisper Small Hi - Kapil Pathak results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 11.0 type: mozilla-foundation/common_voice_11_0 config: hi split: test args: 'config: hi, split: test' metrics: - name: Wer type: wer value: 33.22610683145687 --- # Whisper Small Hi - Kapil Pathak 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: 0.4305 - Wer: 33.2261 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.0878 | 2.44 | 1000 | 0.2926 | 35.2154 | | 0.0193 | 4.89 | 2000 | 0.3489 | 33.7129 | | 0.002 | 7.33 | 3000 | 0.4076 | 33.1880 | | 0.0004 | 9.78 | 4000 | 0.4305 | 33.2261 | ### Framework versions - Transformers 4.39.0.dev0 - Pytorch 2.2.0+cu121 - Datasets 2.17.1 - Tokenizers 0.15.2