--- language: - hi license: apache-2.0 tags: - hf-asr-leaderboard - generated_from_trainer datasets: - mozilla-foundation/common_voice_11_0 metrics: - wer model-index: - name: Whisper Small Jsun Hi - Jiping results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 11.0 type: mozilla-foundation/common_voice_11_0 args: 'config: hi, split: test' metrics: - name: Wer type: wer value: 31.719292305087617 --- # Whisper Small Jsun Hi - Jiping 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: 0.2781 - Wer: 31.7193 ## 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: 4 - 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: 400 - training_steps: 4000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.2077 | 0.61 | 1000 | 0.3197 | 38.8301 | | 0.1096 | 1.22 | 2000 | 0.2827 | 34.3943 | | 0.1044 | 1.83 | 3000 | 0.2675 | 32.4685 | | 0.0519 | 2.45 | 4000 | 0.2781 | 31.7193 | ### Framework versions - Transformers 4.25.0.dev0 - Pytorch 1.12.0+cu102 - Datasets 2.6.1 - Tokenizers 0.13.1