Videomae Base Finetuned Kinetics 0417 Final 5sec Org Ab7 Val Inside Train Balanced Allpretest Re

--- 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-0417_final_5sec_org_ab7_val_inside_train_balanced_allpretest_re 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-0417_final_5sec_org_ab7_val_inside_train_balanced_allpretest_re 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: 0.1627 - Accuracy: 0.9382 ## 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: 86000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:-----:|:---------------:|:--------:| | 0.0088 | 0.0100 | 861 | 0.1426 | 0.9463 | | 3.031 | 1.0100 | 1722 | 0.2207 | 0.9250 | | 0.3094 | 2.0100 | 2583 | 0.5461 | 0.8349 | | 0.0152 | 3.0100 | 3444 | 0.4200 | 0.8863 | | 3.2919 | 4.0100 | 4305 | 0.3855 | 0.8973 | | 0.0007 | 5.0100 | 5166 | 0.2005 | 0.9400 | | 2.4368 | 6.0100 | 6027 | 0.7514 | 0.8239 | | 0.0339 | 7.0100 | 6888 | 0.3068 | 0.9123 | | 0.0082 | 8.0100 | 7749 | 0.3015 | 0.9147 | | 0.0507 | 9.0100 | 8610 | 0.2606 | 0.9329 | | 0.0003 | 10.0100 | 9471 | 0.4086 | 0.9171 | | 0.0179 | 11.0100 | 10332 | 0.2585 | 0.9265 | | 0.0054 | 12.0100 | 11193 | 0.3542 | 0.9155 | | 0.0018 | 13.0100 | 12054 | 0.3996 | 0.9163 | | 0.0728 | 14.0100 | 12915 | 0.4471 | 0.9155 | | 0.0099 | 15.0100 | 13776 | 0.3036 | 0.9336 | ### Framework versions - Transformers 4.48.0 - Pytorch 2.5.1+cu124 - Datasets 3.2.0 - Tokenizers 0.21.0