--- language: - hi license: apache-2.0 tags: - whisper-event - generated_from_trainer datasets: - mozilla-foundation/common_voice_11_0 metrics: - wer model-index: - name: Whisper Small hi- HYDDCSEZ 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: hi metrics: - name: Wer type: wer value: 18.798644812746083 --- # Whisper Small hi- HYDDCSEZ 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: 0.6357 - Wer: 18.7986 ## 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: 64 - 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 | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.0037 | 14.01 | 1000 | 0.4715 | 19.1786 | | 0.0001 | 28.01 | 2000 | 0.5589 | 18.5377 | | 0.0001 | 43.01 | 3000 | 0.6008 | 18.5903 | | 0.0 | 57.01 | 4000 | 0.6234 | 18.7735 | | 0.0 | 72.01 | 5000 | 0.6357 | 18.7986 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.13.0+cu117 - Datasets 2.7.1.dev0 - Tokenizers 0.13.2