--- library_name: transformers license: cc-by-nc-4.0 base_model: MCG-NJU/videomae-large-finetuned-kinetics tags: - generated_from_trainer metrics: - accuracy model-index: - name: CTMAE-P2-V3-3G-S5 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. --> # CTMAE-P2-V3-3G-S5 This model is a fine-tuned version of [MCG-NJU/videomae-large-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-large-finetuned-kinetics) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.7553 - Accuracy: 0.8409 ## 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: 1e-05 - train_batch_size: 2 - eval_batch_size: 2 - 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: 6500 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:----:|:---------------:|:--------:| | 0.6815 | 0.0202 | 131 | 0.7046 | 0.5227 | | 0.4922 | 1.0202 | 262 | 0.9263 | 0.5227 | | 0.6484 | 2.0202 | 393 | 0.7719 | 0.5227 | | 0.6707 | 3.0202 | 524 | 0.7503 | 0.5227 | | 1.1086 | 4.0202 | 655 | 0.7398 | 0.5227 | | 0.6679 | 5.0202 | 786 | 0.6244 | 0.5227 | | 0.7521 | 6.0202 | 917 | 0.7773 | 0.5227 | | 1.7822 | 7.0202 | 1048 | 1.4883 | 0.5227 | | 0.7714 | 8.0202 | 1179 | 1.0682 | 0.5455 | | 0.5244 | 9.0202 | 1310 | 0.7003 | 0.5227 | | 0.7346 | 10.0202 | 1441 | 1.0285 | 0.5 | | 0.4019 | 11.0202 | 1572 | 0.6361 | 0.6364 | | 0.7769 | 12.0202 | 1703 | 0.4666 | 0.7727 | | 0.6358 | 13.0202 | 1834 | 1.3155 | 0.6364 | | 0.5129 | 14.0202 | 1965 | 1.1485 | 0.6818 | | 1.1003 | 15.0202 | 2096 | 0.5102 | 0.7955 | | 0.7943 | 16.0202 | 2227 | 0.6434 | 0.7273 | | 0.363 | 17.0202 | 2358 | 0.9532 | 0.7955 | | 0.2225 | 18.0202 | 2489 | 0.6883 | 0.7273 | | 0.2107 | 19.0202 | 2620 | 0.6559 | 0.8182 | | 1.0048 | 20.0202 | 2751 | 0.9784 | 0.7727 | | 0.4285 | 21.0202 | 2882 | 0.9721 | 0.7273 | | 0.0459 | 22.0202 | 3013 | 0.6200 | 0.8182 | | 0.9143 | 23.0202 | 3144 | 1.4102 | 0.6818 | | 0.426 | 24.0202 | 3275 | 1.4732 | 0.6591 | | 0.8278 | 25.0202 | 3406 | 1.0037 | 0.7955 | | 0.7064 | 26.0202 | 3537 | 0.7553 | 0.8409 | | 0.6217 | 27.0202 | 3668 | 1.5788 | 0.7045 | | 0.6104 | 28.0202 | 3799 | 1.4799 | 0.7045 | | 0.4625 | 29.0202 | 3930 | 2.0381 | 0.6136 | | 0.1935 | 30.0202 | 4061 | 1.8624 | 0.6136 | | 0.3657 | 31.0202 | 4192 | 1.4570 | 0.7273 | | 0.0952 | 32.0202 | 4323 | 1.2123 | 0.8182 | | 0.6802 | 33.0202 | 4454 | 1.1155 | 0.8409 | | 0.1602 | 34.0202 | 4585 | 1.0990 | 0.8182 | | 0.269 | 35.0202 | 4716 | 1.3373 | 0.7727 | | 0.2087 | 36.0202 | 4847 | 1.0545 | 0.7955 | | 0.4447 | 37.0202 | 4978 | 1.1182 | 0.7955 | | 0.803 | 38.0202 | 5109 | 1.9385 | 0.7045 | | 0.685 | 39.0202 | 5240 | 1.5079 | 0.75 | | 0.001 | 40.0202 | 5371 | 1.3848 | 0.7955 | | 0.7371 | 41.0202 | 5502 | 1.8426 | 0.7273 | | 0.0008 | 42.0202 | 5633 | 1.9710 | 0.7273 | | 0.2964 | 43.0202 | 5764 | 2.2087 | 0.7045 | | 0.0008 | 44.0202 | 5895 | 1.5878 | 0.7727 | | 0.0005 | 45.0202 | 6026 | 1.8426 | 0.7273 | | 0.4393 | 46.0202 | 6157 | 1.7193 | 0.75 | | 0.0036 | 47.0202 | 6288 | 1.9741 | 0.7273 | | 0.0005 | 48.0202 | 6419 | 1.8383 | 0.75 | | 0.1776 | 49.0125 | 6500 | 1.8362 | 0.75 | ### Framework versions - Transformers 4.46.2 - Pytorch 2.0.1+cu117 - Datasets 3.0.1 - Tokenizers 0.20.0