Videomae Base Finetuned Kinetics Allkisa Crop Background 0310 Clip Duration Kisapplcroppadding

--- 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-0310-clip_duration-kisapplcroppadding 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-0310-clip_duration-kisapplcroppadding 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: 0.2341 - Accuracy: 0.9172 ## 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: 25400 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:----:|:---------------:|:--------:| | 0.0013 | 0.0100 | 255 | 0.4674 | 0.8421 | | 0.0274 | 1.0100 | 510 | 0.4560 | 0.8289 | | 0.1435 | 2.0100 | 765 | 0.6663 | 0.7650 | | 0.3143 | 3.0100 | 1020 | 1.5072 | 0.6504 | | 0.0054 | 4.0100 | 1275 | 0.6556 | 0.7462 | | 0.0162 | 5.0100 | 1530 | 0.4079 | 0.8759 | | 0.0054 | 6.0100 | 1785 | 0.5968 | 0.8308 | | 0.0001 | 7.0100 | 2040 | 0.7019 | 0.8158 | | 0.0001 | 8.0100 | 2295 | 0.7552 | 0.8289 | | 0.2085 | 9.0100 | 2550 | 0.4732 | 0.8628 | | 0.1964 | 10.0100 | 2805 | 0.6653 | 0.8477 | | 0.0005 | 11.0100 | 3060 | 0.6082 | 0.8383 | | 0.0016 | 12.0100 | 3315 | 0.8231 | 0.8496 | | 0.0002 | 13.0100 | 3570 | 1.1288 | 0.8195 | | 0.0001 | 14.0100 | 3825 | 0.8457 | 0.8496 | | 0.0 | 15.0100 | 4080 | 1.0848 | 0.8252 | ### Framework versions - Transformers 4.48.1 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0