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End of training

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README.md ADDED
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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: 0.0503
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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: 4
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+ - eval_batch_size: 4
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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: 1200
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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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+ | 2.1866 | 0.06 | 75 | 2.0837 | 0.2286 |
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+ | 0.898 | 1.06 | 150 | 0.8424 | 0.6429 |
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+ | 0.4187 | 2.06 | 225 | 0.6812 | 0.7429 |
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+ | 0.3636 | 3.06 | 300 | 0.5211 | 0.8286 |
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+ | 0.1533 | 4.06 | 375 | 0.5294 | 0.8143 |
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+ | 0.136 | 5.06 | 450 | 0.1853 | 0.9286 |
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+ | 0.1537 | 6.06 | 525 | 0.0949 | 0.9714 |
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+ | 0.0734 | 7.06 | 600 | 0.1561 | 0.9571 |
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+ | 0.0039 | 8.06 | 675 | 0.1018 | 0.9857 |
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+ | 0.0042 | 9.06 | 750 | 0.0403 | 0.9857 |
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+ | 0.0028 | 10.06 | 825 | 0.1176 | 0.9714 |
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+ | 0.0082 | 11.06 | 900 | 0.0272 | 0.9857 |
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+ | 0.0022 | 12.06 | 975 | 0.0345 | 0.9857 |
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+ | 0.002 | 13.06 | 1050 | 0.0631 | 0.9857 |
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+ | 0.002 | 14.06 | 1125 | 0.0469 | 0.9714 |
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+ | 0.0095 | 15.06 | 1200 | 0.0503 | 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 4.36.2
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+ - Pytorch 2.1.2+cu121
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+ - Datasets 2.16.0
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+ - Tokenizers 0.15.0
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