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├── checkpoints/ # Training checkpoints
│ ├── CKPT+epoch_*/ # Per-epoch checkpoints
│ ├── CKPT+BEST_WER/ # Best WER checkpoint
│ └── CKPT+FINAL/ # Final checkpoint
├── final_model/ # Transformers-compatible model
│ ├── config.json # Model configuration
│ ├── model.safetensors # Model weights
│ ├── preprocessor_config.json
│ ├── tokenizer_config.json
│ └── ...
├── test_results.json # Test metrics
├── detailed_metrics.json # Detailed training history
├── training_history_speechbrain.png # Training curves
└── training_report_speechbrain.txt # Summary report1import torch
2checkpoint = torch.load('checkpoints/CKPT+BEST_WER/model.ckpt')1from transformers import WhisperForConditionalGeneration, WhisperProcessor
2
3model = WhisperForConditionalGeneration.from_pretrained("./final_model")
4processor = WhisperProcessor.from_pretrained("./final_model")1@article{radford2022robust,
2 title={Robust speech recognition via large-scale weak supervision},
3 author={Radford, Alec and Kim, Jong Wook and Xu, Tao and Brockman, Greg and McLeavey, Christine and Sutskever, Ilya},
4 journal={arXiv preprint arXiv:2212.04356},
5 year={2022}
6}