--- language: - es license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - mozilla-foundation/common_voice_11_0 metrics: - wer model-index: - name: Whisper Small Es - Carlos Gramajo results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 11.0 type: mozilla-foundation/common_voice_11_0 config: es split: None args: 'config: es, split: test' metrics: - name: Wer type: wer value: 14.574495770982434 --- # Whisper Small Es - Carlos Gramajo 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: 0.2965 - Wer: 14.5745 ## 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: 4000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:-------:| | 0.1142 | 1.0309 | 1000 | 0.2672 | 15.0677 | | 0.045 | 2.0619 | 2000 | 0.2705 | 14.4157 | | 0.0185 | 3.0928 | 3000 | 0.2895 | 14.6389 | | 0.0106 | 4.1237 | 4000 | 0.2965 | 14.5745 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.3.1+cu121 - Datasets 2.21.0 - Tokenizers 0.19.1