This model is a fine-tuned version of MCG-NJU/videomae-small-finetuned-ssv2 on an unknown dataset. It achieves the following results on the evaluation set: Loss: 0.6398 Accuracy: 0.7568
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This model is a fine-tuned version of MCG-NJU/videomae-small-finetuned-ssv2 on an unknown dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.0545 | 0.1053 | 20 | 1.0499 | 0.4324 |
| 0.8731 | 1.1053 | 40 | 1.0377 | 0.4865 |
| 0.7354 | 2.1053 | 60 | 0.9788 | 0.5676 |
| 0.6503 | 3.1053 | 80 | 0.9652 | 0.5946 |
| 0.6196 | 4.1053 | 100 | 0.8469 | 0.5946 |
--- library_name: transformers license: cc-by-nc-4.0 base_model: MCG-NJU/videomae-small-finetuned-ssv2 tags: - generated_from_trainer metrics: - accuracy model-index: - name: videomae-small-finetuned-ssv2-finetuned-judo 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-small-finetuned-ssv2-finetuned-judo This model is a fine-tuned version of [MCG-NJU/videomae-small-finetuned-ssv2](https://huggingface.co/MCG-NJU/videomae-small-finetuned-ssv2) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.6398 - Accuracy: 0.7568 ## 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: 16 - eval_batch_size: 16 - 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: 190 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:------:|:----:|:---------------:|:--------:| | 1.0545 | 0.1053 | 20 | 1.0499 | 0.4324 | | 0.8731 | 1.1053 | 40 | 1.0377 | 0.4865 | | 0.7354 | 2.1053 | 60 | 0.9788 | 0.5676 | | 0.6503 | 3.1053 | 80 | 0.9652 | 0.5946 | | 0.6196 | 4.1053 | 100 | 0.8469 | 0.5946 | | 0.5233 | 5.1053 | 120 | 0.7983 | 0.5676 | | 0.4382 | 6.1053 | 140 | 0.7651 | 0.6757 | | 0.2919 | 7.1053 | 160 | 0.7395 | 0.7297 | | 0.3249 | 8.1053 | 180 | 0.6420 | 0.7568 | | 0.2896 | 9.0526 | 190 | 0.6398 | 0.7568 | ### Framework versions - Transformers 4.48.3 - Pytorch 2.5.1+cu124 - Datasets 3.3.2 - Tokenizers 0.21.0
Source context: 4 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo adenhaus/videomae-small-finetuned-ssv2-finetuned-judo
| 0.5233 | 5.1053 | 120 | 0.7983 | 0.5676 |
| 0.4382 | 6.1053 | 140 | 0.7651 | 0.6757 |
| 0.2919 | 7.1053 | 160 | 0.7395 | 0.7297 |
| 0.3249 | 8.1053 | 180 | 0.6420 | 0.7568 |
| 0.2896 | 9.0526 | 190 | 0.6398 | 0.7568 |