Videomae Base Finetuned Kinetics Allkisa Crop Background 0307 Clip Duration Abnormal38

--- 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-allkisa-crop-background-0307-clip_duration-abnormal38 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-allkisa-crop-background-0307-clip_duration-abnormal38 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: 0.1985 - Accuracy: 0.9329 ## 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: 29400 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:----:|:---------------:|:--------:| | 0.0024 | 0.0100 | 295 | 0.2932 | 0.8709 | | 0.0011 | 1.0100 | 590 | 0.6339 | 0.8045 | | 0.0028 | 2.0100 | 885 | 0.7747 | 0.7888 | | 0.0029 | 3.0100 | 1180 | 0.5034 | 0.8551 | | 1.0298 | 4.0100 | 1475 | 0.5480 | 0.8150 | | 0.0248 | 5.0100 | 1770 | 0.3638 | 0.8726 | | 0.0435 | 6.0100 | 2065 | 0.8338 | 0.7976 | | 0.0001 | 7.0100 | 2360 | 0.8290 | 0.7749 | | 0.0004 | 8.0100 | 2655 | 0.5562 | 0.8464 | | 0.0001 | 9.0100 | 2950 | 1.0491 | 0.8080 | | 0.0002 | 10.0100 | 3245 | 0.7868 | 0.8290 | | 0.0197 | 11.0100 | 3540 | 0.6573 | 0.8586 | | 0.0002 | 12.0100 | 3835 | 0.8348 | 0.8325 | | 0.0001 | 13.0100 | 4130 | 0.6864 | 0.8464 | | 0.0001 | 14.0100 | 4425 | 0.6752 | 0.8517 | | 0.0 | 15.0100 | 4720 | 0.8101 | 0.8464 | ### Framework versions - Transformers 4.48.1 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0