ALL RGBCROP Ori16F 8B16F GACWDlr5e 6

--- library_name: transformers license: cc-by-nc-4.0 base_model: MCG-NJU/videomae-base-finetuned-kinetics tags: - generated_from_trainer metrics: - accuracy model-index: - name: ALL_RGBCROP_ori16F-8B16F-GACWDlr5e-6 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. --> # ALL_RGBCROP_ori16F-8B16F-GACWDlr5e-6 This model is a fine-tuned version of [MCG-NJU/videomae-base-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-base-finetuned-kinetics) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.4757 - Accuracy: 0.8443 ## 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: 5e-06 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 16 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - training_steps: 768 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:----:|:---------------:|:--------:| | 0.6952 | 0.0625 | 48 | 0.7022 | 0.5244 | | 0.5982 | 1.0625 | 96 | 0.6475 | 0.6463 | | 0.4329 | 2.0625 | 144 | 0.5911 | 0.7134 | | 0.3752 | 3.0625 | 192 | 0.5338 | 0.7378 | | 0.2202 | 4.0625 | 240 | 0.5109 | 0.75 | | 0.1893 | 5.0625 | 288 | 0.4991 | 0.7439 | | 0.1454 | 6.0625 | 336 | 0.5313 | 0.7439 | | 0.0931 | 7.0625 | 384 | 0.5668 | 0.7439 | | 0.0657 | 8.0625 | 432 | 0.6028 | 0.7622 | | 0.0704 | 9.0625 | 480 | 0.6340 | 0.7744 | | 0.0298 | 10.0625 | 528 | 0.6770 | 0.7683 | | 0.031 | 11.0625 | 576 | 0.7089 | 0.7805 | | 0.0265 | 12.0625 | 624 | 0.7415 | 0.7683 | | 0.0238 | 13.0625 | 672 | 0.7703 | 0.7744 | | 0.0143 | 14.0625 | 720 | 0.7857 | 0.7744 | | 0.0082 | 15.0625 | 768 | 0.7922 | 0.7683 | ### Framework versions - Transformers 4.51.3 - Pytorch 2.6.0+cu124 - Datasets 3.6.0 - Tokenizers 0.21.1