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MAE-CT-CPC-Dicotomized-n0-m1-v8-1

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: beingbatman/MAE-CT-CPC-Dicotomized-v8-n0-m1
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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-n0-m1-v8-1
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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-n0-m1-v8-1
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+
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+ This model is a fine-tuned version of [beingbatman/MAE-CT-CPC-Dicotomized-v8-n0-m1](https://huggingface.co/beingbatman/MAE-CT-CPC-Dicotomized-v8-n0-m1) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8805
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+ - Accuracy: 0.8372
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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: 3500
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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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+ | 0.3313 | 0.02 | 70 | 0.8279 | 0.6875 |
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+ | 0.4602 | 1.02 | 140 | 0.7751 | 0.6562 |
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+ | 0.413 | 2.02 | 210 | 0.9297 | 0.6562 |
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+ | 0.2196 | 3.02 | 280 | 1.3078 | 0.5938 |
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+ | 0.4898 | 4.02 | 350 | 1.2869 | 0.625 |
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+ | 0.1867 | 5.02 | 420 | 1.5884 | 0.625 |
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+ | 0.0394 | 6.02 | 490 | 1.7787 | 0.625 |
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+ | 0.1218 | 7.02 | 560 | 1.7999 | 0.5938 |
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+ | 0.192 | 8.02 | 630 | 1.7295 | 0.625 |
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+ | 0.3974 | 9.02 | 700 | 1.4709 | 0.6562 |
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+ | 0.4529 | 10.02 | 770 | 1.6416 | 0.625 |
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+ | 0.0831 | 11.02 | 840 | 2.0432 | 0.6875 |
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+ | 0.0104 | 12.02 | 910 | 2.1283 | 0.5938 |
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+ | 0.0287 | 13.02 | 980 | 1.8532 | 0.75 |
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+ | 0.0426 | 14.02 | 1050 | 2.0925 | 0.6875 |
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+ | 0.0145 | 15.02 | 1120 | 2.3519 | 0.625 |
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+ | 0.0024 | 16.02 | 1190 | 2.0705 | 0.625 |
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+ | 0.0176 | 17.02 | 1260 | 2.3603 | 0.625 |
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+ | 0.0023 | 18.02 | 1330 | 2.3409 | 0.6562 |
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+ | 0.1111 | 19.02 | 1400 | 2.3461 | 0.625 |
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+ | 0.0002 | 20.02 | 1470 | 2.0998 | 0.6875 |
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+ | 0.0432 | 21.02 | 1540 | 2.2703 | 0.5938 |
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+ | 0.006 | 22.02 | 1610 | 2.3306 | 0.6562 |
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+ | 0.0014 | 23.02 | 1680 | 2.4463 | 0.625 |
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+ | 0.0173 | 24.02 | 1750 | 2.5565 | 0.6562 |
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+ | 0.0001 | 25.02 | 1820 | 2.7107 | 0.625 |
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+ | 0.0001 | 26.02 | 1890 | 3.0925 | 0.5938 |
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+ | 0.1792 | 27.02 | 1960 | 2.5367 | 0.625 |
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+ | 0.0004 | 28.02 | 2030 | 2.9952 | 0.5625 |
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+ | 0.0001 | 29.02 | 2100 | 2.7962 | 0.625 |
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+ | 0.0 | 30.02 | 2170 | 3.1082 | 0.5938 |
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+ | 0.0001 | 31.02 | 2240 | 2.6867 | 0.625 |
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+ | 0.0 | 32.02 | 2310 | 2.6702 | 0.625 |
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+ | 0.0 | 33.02 | 2380 | 3.3403 | 0.5938 |
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+ | 0.0 | 34.02 | 2450 | 3.0539 | 0.625 |
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+ | 0.2031 | 35.02 | 2520 | 2.7333 | 0.6875 |
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+ | 0.0 | 36.02 | 2590 | 2.9420 | 0.5938 |
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+ | 0.0 | 37.02 | 2660 | 2.9199 | 0.6562 |
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+ | 0.0018 | 38.02 | 2730 | 2.8934 | 0.5938 |
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+ | 0.0 | 39.02 | 2800 | 2.8320 | 0.625 |
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+ | 0.0 | 40.02 | 2870 | 2.8381 | 0.625 |
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+ | 0.0 | 41.02 | 2940 | 2.8439 | 0.625 |
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+ | 0.0 | 42.02 | 3010 | 2.8525 | 0.625 |
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+ | 0.0 | 43.02 | 3080 | 2.6921 | 0.5938 |
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+ | 0.0 | 44.02 | 3150 | 2.9580 | 0.625 |
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+ | 0.0 | 45.02 | 3220 | 3.0292 | 0.5938 |
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+ | 0.0 | 46.02 | 3290 | 3.1119 | 0.625 |
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+ | 0.0 | 47.02 | 3360 | 3.1150 | 0.625 |
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+ | 0.0 | 48.02 | 3430 | 3.1127 | 0.625 |
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+ | 0.0 | 49.02 | 3500 | 3.1126 | 0.625 |
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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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