--- license: apache-2.0 tags: - whisper-event - generated_from_trainer datasets: - google/fleurs metrics: - wer model-index: - name: Whisper Large Amharic FLEURS results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: google/fleurs am_et type: google/fleurs config: am_et split: validation args: am_et metrics: - name: Wer type: wer value: 102.94117647058823 --- # Whisper Large Amharic FLEURS This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the google/fleurs am_et dataset. It achieves the following results on the evaluation set: - Loss: 12.2408 - Wer: 102.9412 ## 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: 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 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:--------:| | 0.0 | 1000.0 | 1000 | 8.3822 | 156.0160 | | 0.0 | 2000.0 | 2000 | 9.7961 | 110.4278 | | 0.0 | 3000.0 | 3000 | 12.0014 | 102.8075 | | 0.0 | 4000.0 | 4000 | 12.2633 | 103.3422 | | 0.0 | 5000.0 | 5000 | 12.2408 | 102.9412 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.13.1+cu117 - Datasets 2.8.1.dev0 - Tokenizers 0.13.2