--- license: apache-2.0 tags: - generated_from_trainer datasets: - common_voice_11_0 metrics: - wer model-index: - name: openai/whisper-small results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: common_voice_11_0 type: common_voice_11_0 config: it split: test args: it metrics: - name: Wer type: wer value: 12.502657877950243 --- # 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: 0.2698 - Wer: 12.5027 ## 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: 8e-06 - 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: 6000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.2737 | 2.01 | 1000 | 0.2728 | 13.4097 | | 0.1536 | 4.02 | 2000 | 0.2611 | 12.9897 | | 0.0905 | 6.03 | 3000 | 0.2686 | 12.9273 | | 0.1301 | 8.04 | 4000 | 0.2534 | 12.3040 | | 0.096 | 10.05 | 5000 | 0.2727 | 12.6130 | | 0.0604 | 12.06 | 6000 | 0.2698 | 12.5027 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.13.0+cu117 - Datasets 2.7.1.dev0 - Tokenizers 0.13.2