--- language: - cs license: apache-2.0 tags: - whisper-event - generated_from_trainer datasets: - mozilla-foundation/common_voice_11_0 metrics: - wer model-index: - name: Whisper Large-v2 Czech CV11 v2 results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: mozilla-foundation/common_voice_11_0 cs type: mozilla-foundation/common_voice_11_0 config: cs split: test args: cs metrics: - name: Wer type: wer value: 9.045873924973758 --- # Whisper Large-v2 Czech CV11 v2 This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the mozilla-foundation/common_voice_11_0 cs dataset. It achieves the following results on the evaluation set: - Loss: 0.2120 - Wer: 9.0459 ## Model description Fine tuned with deepspeed optimization and batch_size: 32. ## 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: 8 - seed: 42 - distributed_type: multi-GPU - gradient_accumulation_steps: 2 - total_train_batch_size: 64 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 5000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:------:| | 0.0106 | 4.24 | 1000 | 0.1625 | 9.9888 | | 0.0034 | 8.47 | 2000 | 0.1841 | 9.8304 | | 0.0011 | 12.71 | 3000 | 0.1917 | 9.4031 | | 0.0004 | 16.95 | 4000 | 0.2075 | 9.1177 | | 0.0003 | 21.19 | 5000 | 0.2120 | 9.0459 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.13.0+cu117 - Datasets 2.7.1.dev0 - Tokenizers 0.13.2