--- license: mit base_model: google/vivit-b-16x2-kinetics400 tags: - generated_from_trainer metrics: - accuracy model-index: - name: vivit-b-16x2-kinetics400-finetuned-kinectic results: [] --- # vivit-b-16x2-kinetics400-finetuned-kinectic 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: 0.9264 - Accuracy: 0.7342 ## 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: 1 - eval_batch_size: 1 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - training_steps: 300 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.0732 | 0.17 | 50 | 1.2968 | 0.4702 | | 1.5128 | 1.17 | 100 | 1.0409 | 0.6607 | | 0.1189 | 2.17 | 150 | 0.9205 | 0.6607 | | 0.3398 | 3.17 | 200 | 0.7474 | 0.7440 | | 0.0102 | 4.17 | 250 | 1.0972 | 0.6786 | | 0.0035 | 5.17 | 300 | 0.9135 | 0.7143 | ### Framework versions - Transformers 4.38.1 - Pytorch 2.1.0+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2