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--- |
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license: cc-by-nc-4.0 |
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base_model: MCG-NJU/videomae-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: videomae-base-finetuned-subset-check10 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# videomae-base-finetuned-subset-check10 |
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This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co./MCG-NJU/videomae-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8682 |
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- Accuracy: 0.6343 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- training_steps: 2220 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 1.5175 | 0.03 | 56 | 1.6041 | 0.2074 | |
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| 1.4397 | 1.03 | 112 | 1.4559 | 0.3871 | |
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| 1.464 | 2.03 | 168 | 1.3637 | 0.3963 | |
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| 1.3404 | 3.03 | 224 | 1.2467 | 0.4470 | |
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| 1.3284 | 4.03 | 280 | 1.3115 | 0.3318 | |
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| 1.1598 | 5.03 | 336 | 1.2489 | 0.4470 | |
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| 0.9615 | 6.03 | 392 | 1.3057 | 0.4009 | |
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| 0.9357 | 7.03 | 448 | 0.9201 | 0.6498 | |
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| 0.9785 | 8.03 | 504 | 0.8629 | 0.6774 | |
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| 1.0862 | 9.03 | 560 | 1.0977 | 0.5069 | |
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| 0.9315 | 10.03 | 616 | 0.7868 | 0.7097 | |
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| 0.9404 | 11.03 | 672 | 0.8170 | 0.6728 | |
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| 0.939 | 12.03 | 728 | 0.9246 | 0.6636 | |
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| 0.8205 | 13.03 | 784 | 0.8420 | 0.6866 | |
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| 0.6719 | 14.03 | 840 | 1.0725 | 0.5899 | |
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| 0.8308 | 15.03 | 896 | 0.8683 | 0.6912 | |
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| 0.7554 | 16.03 | 952 | 0.9684 | 0.5991 | |
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| 0.6962 | 17.03 | 1008 | 1.1106 | 0.5484 | |
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| 0.7995 | 18.03 | 1064 | 0.9751 | 0.6498 | |
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| 0.8298 | 19.03 | 1120 | 1.0631 | 0.5300 | |
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| 0.6607 | 20.03 | 1176 | 0.9458 | 0.6175 | |
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| 0.688 | 21.03 | 1232 | 1.0296 | 0.6037 | |
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| 0.5835 | 22.03 | 1288 | 0.8948 | 0.6774 | |
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| 0.6987 | 23.03 | 1344 | 0.7883 | 0.7189 | |
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| 0.4979 | 24.03 | 1400 | 0.7089 | 0.7189 | |
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| 0.6163 | 25.03 | 1456 | 0.7634 | 0.7235 | |
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| 0.6754 | 26.03 | 1512 | 0.9444 | 0.6359 | |
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| 0.6673 | 27.03 | 1568 | 0.8391 | 0.6544 | |
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| 0.4924 | 28.03 | 1624 | 0.8289 | 0.6682 | |
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| 0.6438 | 29.03 | 1680 | 0.9605 | 0.6129 | |
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| 0.5714 | 30.03 | 1736 | 0.8838 | 0.6452 | |
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| 0.6726 | 31.03 | 1792 | 0.8412 | 0.6590 | |
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| 0.5027 | 32.03 | 1848 | 0.8439 | 0.6728 | |
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| 0.4649 | 33.03 | 1904 | 0.9525 | 0.6267 | |
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| 0.6625 | 34.03 | 1960 | 0.7850 | 0.7281 | |
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| 0.5793 | 35.03 | 2016 | 0.8481 | 0.6728 | |
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| 0.6411 | 36.03 | 2072 | 0.8842 | 0.6590 | |
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| 0.6592 | 37.03 | 2128 | 0.8028 | 0.6912 | |
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| 0.5524 | 38.03 | 2184 | 0.8216 | 0.6866 | |
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| 0.5697 | 39.02 | 2220 | 0.8339 | 0.6774 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.1 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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