--- 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-lr3e-06-FULL results: [] --- # ./openai/whisper-medium.en-cit-do015-wd0-lr3e-06-FULL This model is a fine-tuned version of [openai/whisper-medium.en](https://huggingface.co/openai/whisper-medium.en) on the FULL dataset. It achieves the following results on the evaluation set: - Loss: 0.6528 - Wer Ortho: 32.2429 - Wer: 22.4370 ## 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: 3e-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 | |:-------------:|:------:|:----:|:---------------:|:---------:|:-------:| | 1.8096 | 0.4773 | 50 | 1.2178 | 42.1611 | 31.5966 | | 1.1953 | 0.9547 | 100 | 0.9199 | 37.1498 | 27.2773 | | 0.9212 | 1.4320 | 150 | 0.8408 | 34.7486 | 25.2605 | | 0.8448 | 1.9093 | 200 | 0.7837 | 33.6001 | 24.5210 | | 0.7174 | 2.3866 | 250 | 0.7344 | 32.5039 | 22.9076 | | 0.6519 | 2.8640 | 300 | 0.7002 | 33.3391 | 23.4958 | | 0.5866 | 3.3413 | 350 | 0.6802 | 32.2429 | 22.7395 | | 0.5625 | 3.8186 | 400 | 0.6631 | 32.6083 | 22.8067 | | 0.5207 | 4.2959 | 450 | 0.6548 | 32.6779 | 22.8908 | | 0.5059 | 4.7733 | 500 | 0.6528 | 32.2429 | 22.4370 | ### Framework versions - Transformers 4.42.4 - Pytorch 1.13.1+cu117 - Datasets 2.20.0 - Tokenizers 0.19.1