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: 0.5561 - Accuracy: 0.8258 ## 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: 12 - eval_batch_size: 12 - 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: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 2.1993 | 0.25 | 25 | 1.8601 | 0.4143 | | 1.1178 | 1.25 | 50 | 1.0735 | 0.7 | | 0.7208 | 2.25 | 75 | 0.6374 | 0.7857 | | 0.3841 | 3.25 | 100 | 0.5029 | 0.8857 | ### Framework versions - Transformers 4.53.0.dev0 - Pytorch 2.6.0+cu118 - Datasets 2.13.2 - Tokenizers 0.21.1

Source context: 4 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo lissank/videomae-base-finetuned-ucf101-subset