VideoMAE BdSLW60 FrameRate Corrected WITHOUT Augment 20 Epoch RQ GB

--- library_name: transformers license: cc-by-nc-4.0 base_model: MCG-NJU/videomae-base tags: - generated_from_trainer metrics: - accuracy - precision - recall - f1 model-index: - name: VideoMAE_BdSLW60_FrameRate_Corrected_WITHOUT_Augment_20_epoch_RQ_GB 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_BdSLW60_FrameRate_Corrected_WITHOUT_Augment_20_epoch_RQ_GB 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: 1.5110 - Accuracy: 0.75 - Precision: 0.7751 - Recall: 0.75 - F1: 0.7160 ## 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: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - 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: 18560 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |:-------------:|:-------:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:| | 9.37 | 0.0501 | 929 | 2.6435 | 0.3867 | 0.3678 | 0.3867 | 0.3116 | | 1.0137 | 1.0501 | 1858 | 1.1730 | 0.6883 | 0.7046 | 0.6883 | 0.6376 | | 0.2085 | 2.0501 | 2787 | 0.7637 | 0.7817 | 0.7970 | 0.7817 | 0.7487 | | 0.1241 | 3.0501 | 3716 | 1.2059 | 0.7383 | 0.7799 | 0.7383 | 0.7021 | | 0.0466 | 4.0501 | 4645 | 1.5994 | 0.7317 | 0.7389 | 0.7317 | 0.6956 | | 0.2235 | 5.0501 | 5574 | 0.8861 | 0.815 | 0.8428 | 0.815 | 0.7941 | | 0.1335 | 6.0501 | 6503 | 1.6215 | 0.75 | 0.7610 | 0.75 | 0.7153 | | 0.0882 | 7.0501 | 7432 | 1.5239 | 0.7583 | 0.7890 | 0.7583 | 0.7463 | | 0.0716 | 8.0501 | 8361 | 1.4319 | 0.775 | 0.7999 | 0.775 | 0.7471 | | 0.0076 | 9.0501 | 9290 | 1.7182 | 0.7533 | 0.7603 | 0.7533 | 0.7160 | | 0.2277 | 10.0501 | 10219...