--- language: - el license: apache-2.0 tags: - whisper-event - generated_from_trainer - hf-asr-leaderboard datasets: - mozilla-foundation/common_voice_11_0 - google/fleurs metrics: - wer model-index: - name: Whisper Medium El Greco results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 11.0 type: mozilla-foundation/common_voice_11_0 config: el split: test args: el metrics: - name: Wer type: wer value: 13.976597325408619 --- # Whisper Medium El - Greek One This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set: - Loss: 0.4707 - Wer: 13.9766 ## 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: 20 - 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 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.0036 | 10.01 | 1000 | 0.4461 | 15.9082 | | 0.0001 | 20.02 | 2000 | 0.4250 | 14.5245 | | 0.0 | 31.0 | 3000 | 0.4526 | 14.1902 | | 0.0 | 41.01 | 4000 | 0.4657 | 14.1252 | | 0.0 | 52.0 | 5000 | 0.4707 | 13.9766 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.13.0+cu117 - Datasets 2.7.1.dev0 - Tokenizers 0.13.2