--- license: apache-2.0 tags: - generated_from_trainer metrics: - wer model-index: - name: openai/whisper-large-v2 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # openai/whisper-large-v2 This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.8091 - Wer: 17.7875 ## 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 - distributed_type: multi-GPU - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 10000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:-----:|:---------------:|:-------:| | 0.2528 | 0.2 | 2000 | 0.9370 | 22.1311 | | 0.2718 | 0.4 | 4000 | 0.8721 | 24.9294 | | 0.2745 | 0.6 | 6000 | 0.8770 | 20.5292 | | 0.2157 | 0.8 | 8000 | 0.8774 | 18.1018 | | 0.1729 | 1.0 | 10000 | 0.8091 | 17.7875 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.13.0+cu117 - Datasets 2.7.1.dev0 - Tokenizers 0.13.2