Videomae Base Finetuned Kinetics Allkisa Crop Background 0312 Clip Duration Abnormal09

--- 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-0312-clip_duration-abnormal09 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-0312-clip_duration-abnormal09 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: 0.1607 - Accuracy: 0.9361 ## 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: 31000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:----:|:---------------:|:--------:| | 0.0053 | 0.0100 | 311 | 0.3318 | 0.8869 | | 0.0044 | 1.0100 | 622 | 0.4147 | 0.8724 | | 0.0298 | 2.0100 | 933 | 0.3803 | 0.8562 | | 1.1295 | 3.0100 | 1244 | 0.3465 | 0.8740 | | 0.2517 | 4.0100 | 1555 | 0.3669 | 0.8578 | | 0.9808 | 5.0100 | 1866 | 0.3589 | 0.8691 | | 0.0024 | 6.0100 | 2177 | 0.5094 | 0.8401 | | 0.0013 | 7.0100 | 2488 | 0.4606 | 0.8708 | | 0.0027 | 8.0100 | 2799 | 0.5018 | 0.8255 | | 0.7038 | 9.0100 | 3110 | 0.6441 | 0.8288 | | 0.616 | 10.0100 | 3421 | 0.5086 | 0.8627 | ### Framework versions - Transformers 4.48.0 - Pytorch 2.5.1+cu124 - Datasets 3.2.0 - Tokenizers 0.21.0