Videomae Base Finetuned Kinetics 0402 Final 253259 Roi

--- 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: videomae-base-finetuned-kinetics-0402_final_253259_roi 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. --> # videomae-base-finetuned-kinetics-0402_final_253259_roi 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: 0.8553 - Accuracy: 0.7729 ## 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-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Use 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: 0.05 - training_steps: 80100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:-----:|:---------------:|:--------:| | 0.0115 | 0.0100 | 802 | 0.7706 | 0.8360 | | 0.0058 | 1.0100 | 1604 | 0.8429 | 0.8177 | | 0.1527 | 2.0100 | 2406 | 0.3902 | 0.8818 | | 0.0121 | 3.0100 | 3208 | 0.5051 | 0.8673 | | 0.3265 | 4.0100 | 4010 | 0.7498 | 0.7941 | | 0.0034 | 5.0100 | 4812 | 0.5008 | 0.8581 | | 0.0327 | 6.0100 | 5614 | 0.5419 | 0.8513 | | 0.4163 | 7.0100 | 6416 | 0.8579 | 0.7879 | | 0.2185 | 8.0100 | 7218 | 0.6873 | 0.7910 | | 0.0013 | 9.0100 | 8020 | 1.2436 | 0.7605 | | 0.0051 | 10.0100 | 8822 | 1.4545 | 0.7658 | | 0.0334 | 11.0100 | 9624 | 1.2327 | 0.7071 | | 0.0013 | 12.0100 | 10426 | 0.7517 | 0.8261 | | 0.0048 | 13.0100 | 11228 | 0.6028 | 0.8497 | | 1.5951 | 14.0100 | 12030 | 0.8834 | 0.7582 | | 0.1437 | 15.0100 | 12832 | 1.3627 | 0.7361 | | 0.0634 | 16.0100 | 13634 | 1.0872 | 0.7757 | | 0.5734 | 17.0100 | 14436 | 0.9348 | 0.7757 | ### Framework versions - Transformers 4.48.1 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0