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This model is a fine-tuned version of MCG-NJU/videomae-base-finetuned-kinetics on an unknown dataset. It achieves the following results on the evaluation set: Loss: 0.7272 Accuracy: 0.7940
Model source
Source description
This model is a fine-tuned version of MCG-NJU/videomae-base-finetuned-kinetics on an unknown dataset. It achieves the following results on the evaluation set:
More information needed
Sources
1 sourceVerified Sep 18
Model artifacts
1 artifactSource excerpts
2 excerptsMore information needed
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6494 | 0.0087 | 560 | 0.3440 | 0.9036 |
| 0.0736 | 1.0087 | 1120 | 0.6699 | 0.8073 |
| 0.0027 | 2.0087 | 1680 | 0.6421 | 0.8427 |
| 0.9099 | 3.0087 | 2240 | 0.4211 | 0.8809 |
| 0.019 | 4.0087 | 2800 | 0.7363 | 0.8064 |
--- 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: videomae-base-finetuned-kinetics-0404_final_5sec_bbox 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-base-finetuned-kinetics-0404_final_5sec_bbox 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: 0.7272 - Accuracy: 0.7940 ## 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: 8 - eval_batch_size: 8 - seed: 42 - 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: 0.05 - training_steps: 64400 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:----:|:---------------:|:--------:| | 0.6494 | 0.0087 | 560 | 0.3440 | 0.9036 | | 0.0736 | 1.0087 | 1120 | 0.6699 | 0.8073 | | 0.0027 | 2.0087 | 1680 | 0.6421 | 0.8427 | | 0.9099 | 3.0087 | 2240 | 0.4211 | 0.8809 | | 0.019 | 4.0087 | 2800 | 0.7363 | 0.8064 | | 0.5877 | 5.0087 | 3360 | 0.5784 | 0.81 | | 1.6683 | 6.0087 | 3920 | 1.8367 | 0.7073 | | 0.0294 | 7.0087 | 4480 | 0.5584 | 0.87 | | 0.0993 | 8.0087 | 5040 | 0.5706 | 0.8436 | | 0.0422 | 9.0087 | 5600 | 1.3681 | 0.7082 | | 0.004 | 10.0087 | 6160 | 2.1166 | 0.6673 | | 0.0001 | 11.0087 | 6720 | 1.0887 | 0.78 | | 0.766 | 12.0087 | 7280 | 0.9746 | 0.8127 | | 0.0007 | 13.0087 | 7840 | 1.6220 | 0.7191 | | 1.6621 | 14.0087 | 8400 | 0.8806 | 0.7973 | | 0.0004 | 15.0087 | 8960 | 1.0632 | 0.79 | ### Framework versions - Transformers 4.48.1 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0
Source context: 3 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo d2o2ji/videomae-base-finetuned-kinetics-0404_final_5sec_bbox
| 0.5877 | 5.0087 | 3360 | 0.5784 | 0.81 |
| 1.6683 | 6.0087 | 3920 | 1.8367 | 0.7073 |
| 0.0294 | 7.0087 | 4480 | 0.5584 | 0.87 |
| 0.0993 | 8.0087 | 5040 | 0.5706 | 0.8436 |
| 0.0422 | 9.0087 | 5600 | 1.3681 | 0.7082 |
| 0.004 | 10.0087 | 6160 | 2.1166 | 0.6673 |
| 0.0001 | 11.0087 | 6720 | 1.0887 | 0.78 |
| 0.766 | 12.0087 | 7280 | 0.9746 | 0.8127 |
| 0.0007 | 13.0087 | 7840 | 1.6220 | 0.7191 |
| 1.6621 | 14.0087 | 8400 | 0.8806 | 0.7973 |
| 0.0004 | 15.0087 | 8960 | 1.0632 | 0.79 |
