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MAE-CT-CPC-Dicotomized-v6-tricot

Video Classification
Transformers
Safetensors
videomae
Generated from Trainer
Inference Endpoints
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README.md ADDED
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+ ---
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+ library_name: transformers
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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-tricot
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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-tricot
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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: 2.5595
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+ - Accuracy: 0.2564
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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: 3950
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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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+ | 1.1005 | 0.0203 | 80 | 1.1025 | 0.3191 |
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+ | 1.1073 | 1.0203 | 160 | 1.1015 | 0.4043 |
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+ | 1.117 | 2.0203 | 240 | 1.1486 | 0.2340 |
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+ | 1.0481 | 3.0203 | 320 | 1.1603 | 0.1702 |
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+ | 1.0614 | 4.0203 | 400 | 1.2154 | 0.2979 |
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+ | 0.9155 | 5.0203 | 480 | 1.1238 | 0.3830 |
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+ | 0.9109 | 6.0203 | 560 | 1.1734 | 0.4468 |
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+ | 0.6969 | 7.0203 | 640 | 1.2588 | 0.4468 |
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+ | 0.6381 | 8.0203 | 720 | 1.2711 | 0.4255 |
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+ | 0.5455 | 9.0203 | 800 | 1.3974 | 0.3830 |
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+ | 0.4878 | 10.0203 | 880 | 1.2367 | 0.4468 |
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+ | 0.3125 | 11.0203 | 960 | 1.5500 | 0.4468 |
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+ | 0.5886 | 12.0203 | 1040 | 1.7877 | 0.3191 |
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+ | 0.1826 | 13.0203 | 1120 | 1.8124 | 0.3404 |
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+ | 0.3447 | 14.0203 | 1200 | 1.9852 | 0.4681 |
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+ | 0.2065 | 15.0203 | 1280 | 2.3935 | 0.4043 |
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+ | 0.3104 | 16.0203 | 1360 | 2.9981 | 0.3191 |
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+ | 0.3517 | 17.0203 | 1440 | 2.5522 | 0.3830 |
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+ | 0.0988 | 18.0203 | 1520 | 3.1463 | 0.4468 |
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+ | 0.0532 | 19.0203 | 1600 | 2.8538 | 0.4468 |
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+ | 0.1791 | 20.0203 | 1680 | 3.0306 | 0.4468 |
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+ | 0.1584 | 21.0203 | 1760 | 3.4847 | 0.3830 |
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+ | 0.016 | 22.0203 | 1840 | 3.4121 | 0.3191 |
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+ | 0.0012 | 23.0203 | 1920 | 3.8550 | 0.3617 |
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+ | 0.0005 | 24.0203 | 2000 | 3.9055 | 0.4043 |
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+ | 0.0023 | 25.0203 | 2080 | 4.0501 | 0.4255 |
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+ | 0.0009 | 26.0203 | 2160 | 4.2001 | 0.3404 |
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+ | 0.0004 | 27.0203 | 2240 | 4.0130 | 0.3830 |
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+ | 0.0162 | 28.0203 | 2320 | 4.0468 | 0.4043 |
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+ | 0.0073 | 29.0203 | 2400 | 4.1919 | 0.4255 |
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+ | 0.0012 | 30.0203 | 2480 | 4.0004 | 0.4255 |
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+ | 0.0125 | 31.0203 | 2560 | 4.1151 | 0.3830 |
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+ | 0.0005 | 32.0203 | 2640 | 4.3282 | 0.3830 |
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+ | 0.0098 | 33.0203 | 2720 | 4.4689 | 0.3830 |
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+ | 0.0036 | 34.0203 | 2800 | 4.3354 | 0.4043 |
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+ | 0.0002 | 35.0203 | 2880 | 4.4605 | 0.3617 |
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+ | 0.0002 | 36.0203 | 2960 | 4.1586 | 0.4255 |
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+ | 0.0002 | 37.0203 | 3040 | 4.2574 | 0.4043 |
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+ | 0.0002 | 38.0203 | 3120 | 4.6391 | 0.3830 |
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+ | 0.0008 | 39.0203 | 3200 | 4.5526 | 0.3617 |
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+ | 0.0001 | 40.0203 | 3280 | 4.5658 | 0.3830 |
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+ | 0.0001 | 41.0203 | 3360 | 4.5712 | 0.3830 |
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+ | 0.0001 | 42.0203 | 3440 | 4.6019 | 0.3830 |
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+ | 0.0002 | 43.0203 | 3520 | 4.5915 | 0.4043 |
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+ | 0.0001 | 44.0203 | 3600 | 4.6868 | 0.3830 |
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+ | 0.0001 | 45.0203 | 3680 | 4.6619 | 0.3830 |
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+ | 0.0002 | 46.0203 | 3760 | 4.7142 | 0.3617 |
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+ | 0.0002 | 47.0203 | 3840 | 4.6525 | 0.3617 |
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+ | 0.0001 | 48.0203 | 3920 | 4.6684 | 0.3617 |
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+ | 0.0001 | 49.0076 | 3950 | 4.6668 | 0.3617 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.45.2
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 3.0.1
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+ - Tokenizers 0.20.0
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