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MAE-CT-CPC-Dicotomized-v6-Day1

Safetensors
videomae
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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-large-finetuned-kinetics
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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: MAE-CT-CPC-Dicotomized-v6-Day1
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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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+ # MAE-CT-CPC-Dicotomized-v6-Day1
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+
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+ This model is a fine-tuned version of [MCG-NJU/videomae-large-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-large-finetuned-kinetics) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.2706
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+ - Accuracy: 0.7333
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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: 1e-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: 2750
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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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+ | 0.638 | 0.02 | 56 | 0.6488 | 0.64 |
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+ | 0.7032 | 1.02 | 112 | 0.6394 | 0.64 |
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+ | 0.6243 | 2.02 | 168 | 0.5943 | 0.64 |
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+ | 0.6339 | 3.02 | 224 | 0.6504 | 0.6 |
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+ | 0.6566 | 4.02 | 280 | 0.6405 | 0.64 |
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+ | 0.4056 | 5.02 | 336 | 0.6274 | 0.64 |
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+ | 0.3523 | 6.02 | 392 | 0.9109 | 0.64 |
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+ | 0.4581 | 7.02 | 448 | 0.4675 | 0.8 |
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+ | 0.3648 | 8.02 | 504 | 0.5780 | 0.76 |
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+ | 0.4622 | 9.02 | 560 | 1.1120 | 0.64 |
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+ | 0.5836 | 10.02 | 616 | 0.6369 | 0.76 |
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+ | 0.316 | 11.02 | 672 | 0.8769 | 0.64 |
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+ | 0.135 | 12.02 | 728 | 0.6827 | 0.72 |
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+ | 0.0817 | 13.02 | 784 | 0.9667 | 0.64 |
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+ | 0.5254 | 14.02 | 840 | 0.7442 | 0.76 |
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+ | 0.2692 | 15.02 | 896 | 0.5944 | 0.84 |
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+ | 0.0177 | 16.02 | 952 | 1.0163 | 0.76 |
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+ | 0.0386 | 17.02 | 1008 | 0.8789 | 0.76 |
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+ | 0.2142 | 18.02 | 1064 | 1.0580 | 0.68 |
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+ | 0.0653 | 19.02 | 1120 | 0.9189 | 0.72 |
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+ | 0.0004 | 20.02 | 1176 | 1.1913 | 0.76 |
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+ | 0.0006 | 21.02 | 1232 | 1.1668 | 0.72 |
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+ | 0.0006 | 22.02 | 1288 | 1.2782 | 0.76 |
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+ | 0.0003 | 23.02 | 1344 | 1.2591 | 0.76 |
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+ | 0.0004 | 24.02 | 1400 | 1.5768 | 0.72 |
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+ | 0.0431 | 25.02 | 1456 | 1.1632 | 0.8 |
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+ | 0.008 | 26.02 | 1512 | 1.4113 | 0.76 |
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+ | 0.0003 | 27.02 | 1568 | 1.2239 | 0.76 |
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+ | 0.003 | 28.02 | 1624 | 1.7195 | 0.72 |
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+ | 0.3129 | 29.02 | 1680 | 1.9161 | 0.68 |
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+ | 0.0001 | 30.02 | 1736 | 1.4177 | 0.76 |
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+ | 0.0001 | 31.02 | 1792 | 1.4688 | 0.68 |
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+ | 0.0314 | 32.02 | 1848 | 1.4026 | 0.68 |
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+ | 0.0001 | 33.02 | 1904 | 1.5846 | 0.72 |
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+ | 0.0001 | 34.02 | 1960 | 1.4021 | 0.64 |
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+ | 0.0002 | 35.02 | 2016 | 1.5994 | 0.72 |
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+ | 0.0001 | 36.02 | 2072 | 1.4027 | 0.72 |
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+ | 0.0002 | 37.02 | 2128 | 1.3608 | 0.76 |
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+ | 0.0001 | 38.02 | 2184 | 1.3569 | 0.8 |
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+ | 0.0001 | 39.02 | 2240 | 1.4026 | 0.8 |
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+ | 0.0001 | 40.02 | 2296 | 1.4563 | 0.72 |
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+ | 0.0028 | 41.02 | 2352 | 1.3389 | 0.76 |
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+ | 0.0001 | 42.02 | 2408 | 1.3355 | 0.8 |
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+ | 0.0001 | 43.02 | 2464 | 1.3445 | 0.8 |
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+ | 0.0001 | 44.02 | 2520 | 1.3526 | 0.8 |
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+ | 0.0001 | 45.02 | 2576 | 1.3842 | 0.72 |
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+ | 0.0001 | 46.02 | 2632 | 1.3895 | 0.72 |
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+ | 0.0025 | 47.02 | 2688 | 1.4828 | 0.76 |
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+ | 0.0001 | 48.02 | 2744 | 1.4092 | 0.76 |
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+ | 0.2131 | 49.0 | 2750 | 1.4071 | 0.76 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.37.2
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 3.0.1
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+ - Tokenizers 0.15.1
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