Videomae Base Finetuned Judo

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: 1360

Training results

Framework versions

• Transformers 4.48.3
• Pytorch 2.6.0+cu124
• Datasets 3.4.0
• Tokenizers 0.21.0

--- 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-judo 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-judo 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: 0.9681 - Accuracy: 0.6765 ## 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: 1360 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.3504 | 0.1 | 136 | 1.5076 | 0.2353 | | 1.276 | 1.1 | 272 | 1.3571 | 0.4559 | | 1.3092 | 2.1 | 408 | 1.3368 | 0.3676 | | 1.0253 | 3.1 | 544 | 1.2489 | 0.4853 | | 0.8738 | 4.1 | 680 | 1.2059 | 0.4559 | | 0.8798 | 5.1 | 816 | 1.0972 | 0.5441 | | 0.6182 | 6.1 | 952 | 1.0025 | 0.5882 | | 0.6829 | 7.1 | 1088 | 1.0121 | 0.6176 | | 0.387 | 8.1 | 1224 | 1.0217 | 0.6176 | | 0.484 | 9.1 | 1360 | 0.9681 | 0.6765 | ### Framework versions - Transformers 4.48.3 - Pytorch 2.6.0+cu124 - Datasets 3.4.0 - Tokenizers 0.21.0