--- license: apache-2.0 tags: - whisper-event - generated_from_trainer datasets: - google/fleurs metrics: - wer model-index: - name: Whisper Small Icelandic results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: google/fleurs is_is type: google/fleurs config: is_is split: test args: is_is metrics: - name: Wer type: wer value: 66.5053242981607 --- # Whisper Small Icelandic This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the google/fleurs is_is dataset. It achieves the following results on the evaluation set: - Loss: 1.6747 - Wer: 66.5053 ## 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: 3000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:-------:| | 0.0002 | 499.0 | 1000 | 1.6747 | 66.5053 | | 0.0001 | 999.0 | 2000 | 1.7714 | 67.6670 | | 0.0 | 1499.0 | 3000 | 1.8178 | 68.6350 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.13.1+cu117 - Datasets 2.8.1.dev0 - Tokenizers 0.13.2