RALL NoCrop Ori16F 8B16F GACWDlr

--- 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: RALL_NoCrop_ori16F-8B16F-GACWDlr 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. --> # RALL_NoCrop_ori16F-8B16F-GACWDlr 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: 0.5065 - Accuracy: 0.7952 ## 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: 1e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 16 - 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: 768 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:----:|:---------------:|:--------:| | 0.6577 | 0.0625 | 48 | 0.6599 | 0.5828 | | 0.5804 | 1.0625 | 96 | 0.5964 | 0.6687 | | 0.4664 | 2.0625 | 144 | 0.5430 | 0.7362 | | 0.3242 | 3.0625 | 192 | 0.5026 | 0.7607 | | 0.3144 | 4.0625 | 240 | 0.5147 | 0.7791 | | 0.2619 | 5.0625 | 288 | 0.5442 | 0.7730 | | 0.1878 | 6.0625 | 336 | 0.5396 | 0.7791 | | 0.1582 | 7.0625 | 384 | 0.5496 | 0.7791 | | 0.1704 | 8.0625 | 432 | 0.5834 | 0.7730 | | 0.1474 | 9.0625 | 480 | 0.6093 | 0.7914 | | 0.1417 | 10.0625 | 528 | 0.6054 | 0.7914 | | 0.1299 | 11.0625 | 576 | 0.6755 | 0.7791 | | 0.0923 | 12.0625 | 624 | 0.6802 | 0.7791 | | 0.1148 | 13.0625 | 672 | 0.6629 | 0.7914 | | 0.1312 | 14.0625 | 720 | 0.6819 | 0.7914 | ### Framework versions - Transformers 4.52.2 - Pytorch 2.6.0+cu124 - Datasets 2.14.4 - Tokenizers 0.21.1