--- license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - common_voice_11_0 metrics: - wer model-index: - name: whisper-small-en-nonnative results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: common_voice_11_0 type: common_voice_11_0 config: en split: test args: en metrics: - name: Wer type: wer value: 40.75993091537133 --- # whisper-small-en-nonnative 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: 0.4024 - Wer: 40.7599 ## 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: 10000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:-----:|:---------------:|:-------:| | 0.2992 | 0.2 | 1000 | 0.4468 | 29.3898 | | 0.2918 | 0.39 | 2000 | 0.4240 | 27.1733 | | 0.3078 | 0.59 | 3000 | 0.4173 | 28.4974 | | 0.2711 | 0.79 | 4000 | 0.4027 | 24.5538 | | 0.2813 | 0.98 | 5000 | 0.4029 | 28.6413 | | 0.1416 | 1.18 | 6000 | 0.4078 | 25.9931 | | 0.1399 | 1.38 | 7000 | 0.4078 | 28.8140 | | 0.1478 | 1.57 | 8000 | 0.4070 | 31.3759 | | 0.1479 | 1.77 | 9000 | 0.4033 | 33.5636 | | 0.1266 | 1.97 | 10000 | 0.4024 | 40.7599 | ### Framework versions - Transformers 4.37.2 - Pytorch 2.2.0+cu121 - Datasets 2.16.1 - Tokenizers 0.15.1