Videomae Base Finetuned Ucf101 Subset

--- 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-ucf101-subset 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-ucf101-subset 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: 0.4312 - Accuracy: 0.8645 ## 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_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 0.1 - training_steps: 148 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:------:|:----:|:---------------:|:--------:| | 2.1115 | 0.2568 | 38 | 1.8102 | 0.5143 | | 0.8840 | 1.2568 | 76 | 0.9565 | 0.6286 | | 0.4453 | 2.2568 | 114 | 0.4795 | 0.8857 | | 0.2905 | 3.2297 | 148 | 0.3593 | 0.9286 | ### Framework versions - Transformers 5.0.0 - Pytorch 2.10.0+cu128 - Datasets 4.0.0 - Tokenizers 0.22.2

Source context: 7 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo abdelkader9090/videomae-base-finetuned-ucf101-subset

Source context: 3 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo abdelkader9090/videomae-base-finetuned-ucf101-subset