--- language: - eu license: apache-2.0 tags: - whisper-event - generated_from_trainer datasets: - mozilla-foundation/common_voice_13_0 metrics: - wer model-index: - name: Whisper Small Basque results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: mozilla-foundation/common_voice_13_0 eu type: mozilla-foundation/common_voice_13_0 config: eu split: test args: eu metrics: - name: Wer type: wer value: 18.775568066750374 --- # Whisper Small Basque This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_13_0 eu dataset. It achieves the following results on the evaluation set: - Loss: 0.3812 - Wer: 18.7756 ## 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: 32 - eval_batch_size: 16 - 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 | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.1413 | 2.04 | 1000 | 0.3178 | 22.0139 | | 0.0181 | 4.07 | 2000 | 0.3376 | 20.2864 | | 0.0044 | 7.02 | 3000 | 0.3603 | 18.8768 | | 0.0016 | 9.06 | 4000 | 0.3812 | 18.7756 | | 0.0012 | 12.01 | 5000 | 0.3914 | 18.8302 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.13.1+cu117 - Datasets 2.8.1.dev0 - Tokenizers 0.13.2