--- language: - eu license: apache-2.0 base_model: openai/whisper-small 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: 18.417108833893636 --- # 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: 0.3390 - Wer: 18.4171 ## 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: 5000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.2826 | 1.04 | 1000 | 0.3472 | 24.9342 | | 0.0872 | 2.07 | 2000 | 0.3012 | 20.2661 | | 0.0275 | 3.11 | 3000 | 0.3085 | 19.3021 | | 0.0086 | 4.14 | 4000 | 0.3297 | 18.7513 | | 0.0051 | 6.01 | 5000 | 0.3390 | 18.4171 | ### Framework versions - Transformers 4.33.0.dev0 - Pytorch 2.0.1+cu117 - Datasets 2.14.4 - Tokenizers 0.13.3