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: 0.2697 - Accuracy: 0.9286 ## 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: 4 - eval_batch_size: 4 - 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: 300 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.7277 | 0.25 | 75 | 1.3769 | 0.5571 | | 0.8952 | 1.25 | 150 | 0.8913 | 0.6571 | | 0.3108 | 2.25 | 225 | 0.3952 | 0.8857 | | 0.2449 | 3.25 | 300 | 0.2697 | 0.9286 | ### Framework versions - Transformers 4.48.3 - Pytorch 2.0.0+cu117 - Datasets 3.3.2 - Tokenizers 0.21.0

Source context: 12 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo salt-mania22/videomae-base-finetuned-ucf101-subset