--- library_name: transformers license: cc-by-nc-4.0 base_model: MCG-NJU/videomae-base tags: - generated_from_trainer metrics: - accuracy model-index: - name: videomae-base-nicole 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-nicole This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.8055 - Accuracy: 0.7969 ## 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: 0.1 - training_steps: 500 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.368 | 0.102 | 51 | 1.4286 | 0.2903 | | 1.1282 | 1.102 | 102 | 1.0812 | 0.4516 | | 0.8288 | 2.102 | 153 | 1.4727 | 0.4194 | | 0.3846 | 3.102 | 204 | 1.1547 | 0.6774 | | 0.3053 | 4.102 | 255 | 1.1199 | 0.6774 | | 0.0898 | 5.102 | 306 | 0.6689 | 0.7742 | | 0.304 | 6.102 | 357 | 0.6001 | 0.8065 | | 0.1134 | 7.102 | 408 | 0.5982 | 0.8710 | | 0.0641 | 8.102 | 459 | 0.4034 | 0.9032 | | 0.0834 | 9.082 | 500 | 0.3761 | 0.9032 | ### Framework versions - Transformers 4.46.2 - Pytorch 2.0.1+cu117 - Datasets 3.1.0 - Tokenizers 0.20.3