ViViT BdSLW60 FrameRate Corrected With Augment 20 Epch

--- library_name: transformers license: mit base_model: google/vivit-b-16x2-kinetics400 tags: - generated_from_trainer metrics: - accuracy - precision - recall - f1 model-index: - name: ViViT_BdSLW60_FrameRate_Corrected_with_Augment_20_epch 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. --> # ViViT_BdSLW60_FrameRate_Corrected_with_Augment_20_epch This model is a fine-tuned version of [google/vivit-b-16x2-kinetics400](https://huggingface.co/google/vivit-b-16x2-kinetics400) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.0009 - Accuracy: 0.8117 - Precision: 0.8529 - Recall: 0.8117 - F1: 0.7868 ## 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 | |:-------------:|:-------:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:| | 4.1133 | 0.0501 | 929 | 1.3796 | 0.785 | 0.7920 | 0.785 | 0.7528 | | 0.457 | 1.0501 | 1858 | 0.6823 | 0.805 | 0.8022 | 0.805 | 0.7825 | | 0.127 | 2.0501 | 2787 | 0.4044 | 0.875 | 0.9070 | 0.875 | 0.8649 | | 0.1407 | 3.0501 | 3716 | 0.5490 | 0.8817 | 0.9039 | 0.8817 | 0.8715 | | 0.1246 | 4.0501 | 4645 | 0.7160 | 0.835 | 0.8687 | 0.835 | 0.8213 | | 0.2027 | 5.0501 | 5574 | 0.7256 | 0.8383 | 0.8751 | 0.8383 | 0.8290 | | 0.0732 | 6.0501 | 6503 | 0.5921 | 0.8533 | 0.8551 | 0.8533 | 0.8276 | | 0.1227 | 7.0501 | 7432 | 0.4519 | 0.9133 | 0.9339 | 0.9133 | 0.9038 | | 0.008 | 8.0501 | 8361 | 0.5257 | 0.8817 | 0.8921 | 0.8817 | 0.8718 | | 0.0305 | 9.0501 | 9290 | 0.4730 | 0.875 | 0.9054 | 0.875 | 0.8693 | | 0.0408 | 10.0501 | 10219 | 0...