--- license: apache-2.0 language: - eu tags: - whisper-event - generated_from_trainer datasets: - mozilla-foundation/common_voice_11_0 metrics: - wer model-index: - name: openai/whisper-small results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: mozilla-foundation/common_voice_11_0 eu type: mozilla-foundation/common_voice_11_0 config: eu split: test args: eu metrics: - name: Wer type: wer value: 19.766305675433596 --- # openai/whisper-small Basque-Euskera 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: 0.4485 - Wer: 19.7663 ## 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: 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: 5000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.048 | 4.04 | 1000 | 0.3402 | 21.7816 | | 0.0047 | 9.03 | 2000 | 0.3862 | 20.1694 | | 0.0012 | 14.02 | 3000 | 0.4221 | 19.7419 | | 0.0008 | 19.02 | 4000 | 0.4411 | 19.7174 | | 0.0006 | 24.01 | 5000 | 0.4485 | 19.7663 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.13.0+cu117 - Datasets 2.7.1.dev0 - Tokenizers 0.13.2