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best_model.pth: released checkpointsha256.txt: checksum for the checkpointlogs/train.log: selected training logresults/per_class_acc_lrw1000_val.csv: per-class validation summaryplots/learning_curve.png: learning curve exported from trainingtorch.compile: disabled| Dataset | Split | Metric | Value |
|---|---|---|---|
| LRW-1000 | Validation | Top-1 Accuracy | 55.29% |
1python inference.py \
2 --dataset lrw1000 \
3 --pkl_path /path/to/sample.pkl \
4 --checkpoint /path/to/best_model.pth \
5 --gpu 0best_model_for_lrw1000.pth and train_lrw1000.log1@article{wu2022lip,
2 title={A Lip Reading Method Based on 3D Convolutional Vision Transformer},
3 author={Wu, Jiafeng and others},
4 journal={IEEE Access},
5 year={2022}
6}