Videomae Base Finetuned Sdfvd Plus Alpha

--- 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-finetuned-sdfvd_plus_alpha 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-finetuned-sdfvd_plus_alpha 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: 0.6382 - Accuracy: 0.6115 ## 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 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: 68 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:------:|:----:|:---------------:|:--------:| | 0.7686 | 0.2647 | 18 | 0.6327 | 0.7742 | | 0.6917 | 1.2647 | 36 | 0.5886 | 0.7419 | | 0.6434 | 2.2647 | 54 | 0.5320 | 0.8 | | 0.6342 | 3.2059 | 68 | 0.5144 | 0.8194 | ### Framework versions - Transformers 4.50.3 - Pytorch 2.6.0+cu118 - Datasets 3.5.0 - Tokenizers 0.21.1

Source context: 2 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo cocovani/videomae-base-finetuned-sdfvd_plus_alpha