--- library_name: transformers license: cc-by-nc-4.0 base_model: MCG-NJU/videomae-base-finetuned-kinetics tags: - generated_from_trainer metrics: - accuracy model-index: - name: picth_vision_checkpoint_3 results: [] --- # picth_vision_checkpoint_3 This model is a fine-tuned version of [MCG-NJU/videomae-base-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-base-finetuned-kinetics) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0385 - Accuracy: 0.9965 ## 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: 15690 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 0.1317 | 0.2 | 3138 | 0.1713 | 0.9632 | | 0.0002 | 1.2 | 6276 | 0.0348 | 0.9956 | | 0.026 | 2.2 | 9414 | 0.0616 | 0.9904 | | 0.0 | 3.2 | 12552 | 0.0348 | 0.9965 | | 0.0 | 4.2 | 15690 | 0.0385 | 0.9965 | ### Framework versions - Transformers 4.57.1 - Pytorch 2.6.0+cu124 - Datasets 4.4.1 - Tokenizers 0.22.1