--- language: - es license: apache-2.0 base_model: openai/whisper-base tags: - whisper-event - generated_from_trainer datasets: - mozilla-foundation/common_voice_13_0 metrics: - wer model-index: - name: Whisper Base Spanish results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: mozilla-foundation/common_voice_13_0 es type: mozilla-foundation/common_voice_13_0 config: es split: test args: es metrics: - name: Wer type: wer value: 13.531181636803376 --- # Whisper Base Spanish This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mozilla-foundation/common_voice_13_0 es dataset. It achieves the following results on the evaluation set: - Loss: 0.3281 - Wer: 13.5312 ## 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: 2.5e-05 - train_batch_size: 128 - eval_batch_size: 64 - 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 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.2173 | 4.0 | 1000 | 0.3409 | 14.8123 | | 0.0955 | 8.01 | 2000 | 0.3377 | 15.4269 | | 0.1647 | 12.01 | 3000 | 0.3393 | 14.5602 | | 0.0986 | 16.01 | 4000 | 0.3281 | 13.5312 | | 0.1272 | 20.02 | 5000 | 0.3423 | 13.7596 | ### Framework versions - Transformers 4.33.0.dev0 - Pytorch 2.0.1+cu117 - Datasets 2.14.4 - Tokenizers 0.13.3