--- 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_RGBCROP_Aug16F-2DO2 results: [] --- # RALL_RGBCROP_Aug16F-2DO2 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: 0.3981 - Accuracy: 0.8173 ## 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-06 - train_batch_size: 8 - eval_batch_size: 8 - 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: 3462 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:------:|:----:|:---------------:|:--------:| | 0.5351 | 0.0835 | 289 | 0.6050 | 0.7444 | | 0.3295 | 1.0835 | 578 | 0.4755 | 0.7812 | | 0.2241 | 2.0835 | 867 | 0.4739 | 0.7853 | | 0.1654 | 3.0835 | 1156 | 0.5105 | 0.7914 | | 0.0344 | 4.0835 | 1445 | 0.6131 | 0.7751 | | 0.0831 | 5.0835 | 1734 | 0.6195 | 0.7812 | | 0.1841 | 6.0835 | 2023 | 0.6657 | 0.7812 | | 0.0859 | 7.0835 | 2312 | 0.7488 | 0.7791 | ### Framework versions - Transformers 4.51.3 - Pytorch 2.6.0+cu124 - Datasets 3.6.0 - Tokenizers 0.21.1