--- license: apache-2.0 tags: - generated_from_trainer - hf-asr-leaderboard - whisper-event datasets: - common_voice_11_0 metrics: - wer model-index: - name: openai/whisper-medium results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: mozilla-foundation/common_voice_11_0 type: mozilla-foundation/common_voice_11_0 args: 'config: el, split: test' metrics: - name: Wer type: wer value: 11.469167904903417 --- # openai/whisper-medium 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: 0.3367 - Wer: 11.4692 ## 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: 32 - 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 | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.0108 | 4.04 | 1000 | 0.2423 | 12.7600 | | 0.0013 | 9.04 | 2000 | 0.2810 | 11.9799 | | 0.0001 | 14.04 | 3000 | 0.3152 | 11.5435 | | 0.0001 | 19.04 | 4000 | 0.3304 | 11.4320 | | 0.0001 | 24.04 | 5000 | 0.3367 | 11.4692 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.13.0+cu117 - Datasets 2.7.1.dev0 - Tokenizers 0.13.2