--- license: apache-2.0 tags: - whisper-event - hf-asr-leaderboard - generated_from_trainer datasets: - mozilla-foundation/common_voice_11_0 metrics: - wer base_model: openai/whisper-small model-index: - name: openai/whisper-small results: - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: mozilla-foundation/common_voice_11_0 type: mozilla-foundation/common_voice_11_0 config: hu split: test metrics: - type: wer value: 30.637414764304772 name: Wer --- # openai/whisper-small 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: 0.5649 - Wer: 30.6374 ## 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: 32 - 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 | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.0182 | 7.01 | 1000 | 0.4546 | 31.4735 | | 0.0023 | 14.02 | 2000 | 0.5045 | 31.0910 | | 0.0008 | 22.01 | 3000 | 0.5318 | 30.2816 | | 0.0006 | 29.02 | 4000 | 0.5585 | 30.5989 | | 0.0004 | 37.01 | 5000 | 0.5649 | 30.6374 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.13.0+cu117 - Datasets 2.7.1 - Tokenizers 0.13.2