--- language: - en license: apache-2.0 base_model: openai/whisper-medium.en tags: - generated_from_trainer metrics: - wer model-index: - name: ./openai/whisper-medium.en-cit-do015-wd0-lr1e-06-1000 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-medium.en-cit-do015-wd0-lr1e-06-1000 This model is a fine-tuned version of [openai/whisper-medium.en](https://huggingface.co/openai/whisper-medium.en) on the SF 1000 dataset. It achieves the following results on the evaluation set: - Loss: 0.6953 - Wer Ortho: 26.2768 - Wer: 14.7572 ## 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-06 - train_batch_size: 4 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 100 - training_steps: 500 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |:-------------:|:------:|:----:|:---------------:|:---------:|:-------:| | No log | 0.4444 | 25 | 1.5811 | 45.2632 | 31.9044 | | 1.7463 | 0.8889 | 50 | 1.3848 | 39.1033 | 27.0106 | | 1.7463 | 1.3333 | 75 | 1.2178 | 35.7505 | 23.0273 | | 1.3387 | 1.7778 | 100 | 1.0166 | 36.1014 | 23.4446 | | 1.3387 | 2.2222 | 125 | 0.8784 | 31.9298 | 19.1958 | | 0.988 | 2.6667 | 150 | 0.8340 | 30.8382 | 18.4750 | | 0.988 | 3.1111 | 175 | 0.8027 | 30.3314 | 17.7162 | | 0.8856 | 3.5556 | 200 | 0.7812 | 29.6686 | 17.4127 | | 0.8856 | 4.0 | 225 | 0.7651 | 30.1365 | 17.6783 | | 0.7927 | 4.4444 | 250 | 0.7515 | 29.2008 | 16.8816 | | 0.7927 | 4.8889 | 275 | 0.7402 | 28.2651 | 15.6677 | | 0.7482 | 5.3333 | 300 | 0.7300 | 27.9922 | 15.5159 | | 0.7482 | 5.7778 | 325 | 0.7217 | 27.8752 | 15.6677 | | 0.7275 | 6.2222 | 350 | 0.7153 | 27.4854 | 15.4021 | | 0.7275 | 6.6667 | 375 | 0.7085 | 27.3684 | 15.3642 | | 0.7003 | 7.1111 | 400 | 0.7041 | 26.6277 | 14.6813 | | 0.7003 | 7.5556 | 425 | 0.7002 | 26.3158 | 14.7572 | | 0.6763 | 8.0 | 450 | 0.6973 | 26.2378 | 14.6055 | | 0.6763 | 8.4444 | 475 | 0.6963 | 26.4327 | 14.7951 | | 0.6687 | 8.8889 | 500 | 0.6953 | 26.2768 | 14.7572 | ### Framework versions - Transformers 4.42.3 - Pytorch 1.13.1+cu117 - Datasets 2.20.0 - Tokenizers 0.19.1