--- 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-constant results: [] --- # RALL_RGBCROP_Aug16F-constant 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: 0.5833 - Accuracy: 0.8514 ## 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: constant - lr_scheduler_warmup_ratio: 0.1 - training_steps: 3462 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:------:|:----:|:---------------:|:--------:| | 0.2308 | 0.0835 | 289 | 0.4732 | 0.7894 | | 0.178 | 1.0835 | 578 | 0.6181 | 0.8098 | | 0.0211 | 2.0835 | 867 | 0.7851 | 0.8364 | | 0.0035 | 3.0835 | 1156 | 0.9092 | 0.8323 | | 0.0047 | 4.0835 | 1445 | 0.9882 | 0.8200 | | 0.0002 | 5.0835 | 1734 | 1.0325 | 0.8323 | | 0.0004 | 6.0835 | 2023 | 1.1194 | 0.8221 | ### Framework versions - Transformers 4.51.3 - Pytorch 2.6.0+cu124 - Datasets 3.6.0 - Tokenizers 0.21.1