--- language: - cs license: apache-2.0 tags: - whisper-event - hf-asr-leaderboard - generated_from_trainer datasets: - mozilla-foundation/common_voice_11_0 metrics: - wer base_model: openai/whisper-medium model-index: - name: Whisper Medium Czech CV11 results: - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: mozilla-foundation/common_voice_11_0 type: mozilla-foundation/common_voice_11_0 config: cs split: test metrics: - type: wer value: 11.689339690370561 name: Wer --- # Whisper Medium Czech CV11 This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_11_0 cs dataset. It achieves the following results on the evaluation set: - Loss: 0.2537 - Wer: 11.6893 ## 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: 16 - 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 | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.0384 | 2.02 | 1000 | 0.2167 | 13.5467 | | 0.0061 | 4.03 | 2000 | 0.2373 | 12.9172 | | 0.0018 | 6.05 | 3000 | 0.2407 | 12.0409 | | 0.0007 | 8.07 | 4000 | 0.2463 | 11.7685 | | 0.0003 | 10.09 | 5000 | 0.2537 | 11.6893 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.13.0+cu117 - Datasets 2.7.1.dev0 - Tokenizers 0.13.2