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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: 0.2477 Accuracy: 0.9053
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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:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1532 | 0.0100 | 645 | 0.2212 | 0.9151 |
| 0.0051 | 1.0100 | 1290 | 0.8680 | 0.7644 |
| 0.2625 | 2.0100 | 1935 | 0.4553 | 0.8616 |
| 0.0155 | 3.0100 | 2580 | 0.4682 | 0.8643 |
| 0.021 | 4.0100 | 3225 | 0.6284 | 0.8196 |
--- 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-0403_final_5sec 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-0403_final_5sec 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: 0.2477 - Accuracy: 0.9053 ## 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 | |:-------------:|:-------:|:-----:|:---------------:|:--------:| | 0.1532 | 0.0100 | 645 | 0.2212 | 0.9151 | | 0.0051 | 1.0100 | 1290 | 0.8680 | 0.7644 | | 0.2625 | 2.0100 | 1935 | 0.4553 | 0.8616 | | 0.0155 | 3.0100 | 2580 | 0.4682 | 0.8643 | | 0.021 | 4.0100 | 3225 | 0.6284 | 0.8196 | | 0.6406 | 5.0100 | 3870 | 0.3939 | 0.9116 | | 1.0417 | 6.0100 | 4515 | 1.1531 | 0.7898 | | 0.0027 | 7.0100 | 5160 | 0.7326 | 0.8152 | | 0.0017 | 8.0100 | 5805 | 0.5727 | 0.8809 | | 0.0009 | 9.0100 | 6450 | 0.4952 | 0.8949 | | 0.0077 | 10.0100 | 7095 | 0.7302 | 0.8371 | | 0.0011 | 11.0100 | 7740 | 0.8304 | 0.8100 | | 0.0002 | 12.0100 | 8385 | 0.8539 | 0.8135 | | 0.0002 | 13.0100 | 9030 | 1.4690 | 0.7434 | | 0.9484 | 14.0100 | 9675 | 0.7860 | 0.8319 | | 0.0145 | 15.0100 | 10320 | 1.3528 | 0.7758 | ### Framework versions - Transformers 4.48.1 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0
Source context: 2 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo d2o2ji/videomae-base-finetuned-kinetics-0403_final_5sec
| 0.6406 | 5.0100 | 3870 | 0.3939 | 0.9116 |
| 1.0417 | 6.0100 | 4515 | 1.1531 | 0.7898 |
| 0.0027 | 7.0100 | 5160 | 0.7326 | 0.8152 |
| 0.0017 | 8.0100 | 5805 | 0.5727 | 0.8809 |
| 0.0009 | 9.0100 | 6450 | 0.4952 | 0.8949 |
| 0.0077 | 10.0100 | 7095 | 0.7302 | 0.8371 |
| 0.0011 | 11.0100 | 7740 | 0.8304 | 0.8100 |
| 0.0002 | 12.0100 | 8385 | 0.8539 | 0.8135 |
| 0.0002 | 13.0100 | 9030 | 1.4690 | 0.7434 |
| 0.9484 | 14.0100 | 9675 | 0.7860 | 0.8319 |
| 0.0145 | 15.0100 | 10320 | 1.3528 | 0.7758 |
