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update model card README.md

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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-ucf101-subset
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+ results: []
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+ ---
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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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+
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+ # videomae-base-finetuned-ucf101-subset
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+
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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: 0.0480
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+ - Accuracy: 0.9857
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-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: 600
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 2.2995 | 0.06 | 38 | 2.1143 | 0.3 |
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+ | 1.6428 | 1.06 | 76 | 1.5030 | 0.3429 |
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+ | 0.6261 | 2.06 | 114 | 0.8121 | 0.6286 |
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+ | 0.4044 | 3.06 | 152 | 0.4910 | 0.7714 |
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+ | 0.3236 | 4.06 | 190 | 0.4558 | 0.8714 |
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+ | 0.1865 | 5.06 | 228 | 0.6773 | 0.8 |
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+ | 0.1479 | 6.06 | 266 | 0.1813 | 0.9571 |
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+ | 0.0418 | 7.06 | 304 | 0.1312 | 0.9714 |
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+ | 0.0718 | 8.06 | 342 | 0.2473 | 0.9286 |
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+ | 0.0596 | 9.06 | 380 | 0.1378 | 0.9714 |
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+ | 0.0079 | 10.06 | 418 | 0.0308 | 0.9857 |
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+ | 0.0134 | 11.06 | 456 | 0.0329 | 1.0 |
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+ | 0.0083 | 12.06 | 494 | 0.0310 | 1.0 |
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+ | 0.0394 | 13.06 | 532 | 0.0543 | 0.9714 |
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+ | 0.004 | 14.06 | 570 | 0.0492 | 0.9857 |
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+ | 0.0043 | 15.05 | 600 | 0.0480 | 0.9857 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.31.0
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+ - Pytorch 1.10.0+cu113
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+ - Datasets 2.14.4
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+ - Tokenizers 0.13.3