Videomae Small Finetuned Kinetics Finetuned Judo

--- library_name: transformers tags: - generated_from_trainer metrics: - accuracy model-index: - name: videomae-small-finetuned-kinetics-finetuned-judo 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-small-finetuned-kinetics-finetuned-judo This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.5617 - Accuracy: 0.7838 ## 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: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Use OptimizerNames.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: 0.1 - training_steps: 380 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:----:|:---------------:|:--------:| | 0.8417 | 0.0526 | 20 | 0.9854 | 0.5135 | | 0.6987 | 1.0526 | 40 | 0.9204 | 0.5135 | | 0.6783 | 2.0526 | 60 | 0.8633 | 0.5135 | | 0.4297 | 3.0526 | 80 | 0.8381 | 0.5135 | | 0.4407 | 4.0526 | 100 | 0.7284 | 0.6216 | | 0.3272 | 5.0526 | 120 | 0.7143 | 0.7568 | | 0.2406 | 6.0526 | 140 | 0.7214 | 0.7027 | | 0.2543 | 7.0526 | 160 | 0.4753 | 0.7838 | | 0.1978 | 8.0526 | 180 | 0.7151 | 0.7568 | | 0.124 | 9.0526 | 200 | 0.5700 | 0.7297 | | 0.1031 | 10.0526 | 220 | 0.6495 | 0.7027 | | 0.0994 | 11.0526 | 240 | 0.4222 | 0.8378 | | 0.0674 | 12.0526 | 260 | 0.6267 | 0.7568 | | 0.0462 | 13.0526 | 280 | 0.6330 | 0.7568 | | 0.0419 | 14.0526 | 300 | 0.5131 | 0.8108 | | 0.0264 | 15.0526 | 320 | 0.4656 | 0.8378 | | 0.0347 | 16.0526 | 340 | 0.5933 | 0.7838 | | 0.0287 | 17.0526 | 360 | 0.5434 | 0.7568 | | 0.0176 | 18.0526 | 380 | 0.5617 | 0.7838 | ### Framework versions - Transformers 4.48.3 - Pytorch 2.5.1+cu124 - Datasets 3.3.2 - Tokenizers 0.21.0