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okiane
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timeSformer

Video Classification
Transformers
Safetensors
videomae
Generated from Trainer
Inference Endpoints
Model card Files Community
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  2. model.safetensors +1 -1
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-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: timeSformer
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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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+ # timeSformer
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+
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+ This model is a fine-tuned version of [MCG-NJU/videomae-base-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-base-finetuned-kinetics) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 7.8889
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+ - Accuracy: 0.0052
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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: 0.005
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+ - train_batch_size: 288
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+ - eval_batch_size: 288
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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: 740
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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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+ | 3.8418 | 0.0135 | 10 | 5.5898 | 0.0122 |
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+ | 3.1132 | 1.0135 | 20 | 5.8064 | 0.0052 |
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+ | 3.1265 | 2.0135 | 30 | 5.9893 | 0.0087 |
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+ | 3.1378 | 3.0135 | 40 | 5.8669 | 0.0017 |
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+ | 3.1408 | 4.0135 | 50 | 6.0782 | 0.0 |
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+ | 3.0995 | 5.0135 | 60 | 5.9832 | 0.0 |
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+ | 3.0778 | 6.0135 | 70 | 5.6949 | 0.0486 |
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+ | 3.0765 | 7.0135 | 80 | 5.8415 | 0.0017 |
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+ | 3.0689 | 8.0135 | 90 | 5.9740 | 0.0017 |
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+ | 3.0093 | 9.0135 | 100 | 5.8951 | 0.0052 |
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+ | 3.021 | 10.0135 | 110 | 6.1976 | 0.0052 |
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+ | 2.9475 | 11.0135 | 120 | 6.4536 | 0.0191 |
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+ | 2.9468 | 12.0135 | 130 | 6.5053 | 0.0 |
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+ | 2.9593 | 13.0135 | 140 | 6.1705 | 0.0139 |
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+ | 2.9632 | 14.0135 | 150 | 6.5190 | 0.0017 |
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+ | 2.9551 | 15.0135 | 160 | 6.6961 | 0.0017 |
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+ | 3.0157 | 16.0135 | 170 | 6.0960 | 0.0208 |
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+ | 3.0034 | 17.0135 | 180 | 6.5592 | 0.0052 |
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+ | 2.9783 | 18.0135 | 190 | 6.4399 | 0.0365 |
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+ | 2.9608 | 19.0135 | 200 | 6.4748 | 0.0035 |
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+ | 2.9909 | 20.0135 | 210 | 6.3702 | 0.0035 |
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+ | 2.9598 | 21.0135 | 220 | 6.5077 | 0.0 |
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+ | 2.9552 | 22.0135 | 230 | 7.4796 | 0.0069 |
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+ | 3.0327 | 23.0135 | 240 | 6.5649 | 0.0 |
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+ | 3.0028 | 24.0135 | 250 | 6.6634 | 0.0087 |
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+ | 2.9237 | 25.0135 | 260 | 6.8856 | 0.0 |
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+ | 2.9411 | 26.0135 | 270 | 6.9620 | 0.0017 |
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+ | 2.9281 | 27.0135 | 280 | 6.9007 | 0.0069 |
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+ | 2.9255 | 28.0135 | 290 | 7.0261 | 0.0017 |
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+ | 2.9621 | 29.0135 | 300 | 6.5056 | 0.0 |
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+ | 2.9419 | 30.0135 | 310 | 6.9045 | 0.0035 |
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+ | 2.978 | 31.0135 | 320 | 6.8059 | 0.0122 |
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+ | 3.0299 | 32.0135 | 330 | 6.6262 | 0.0017 |
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+ | 3.0313 | 33.0135 | 340 | 6.6773 | 0.0 |
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+ | 2.995 | 34.0135 | 350 | 6.7126 | 0.0 |
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+ | 2.9588 | 35.0135 | 360 | 6.4966 | 0.0035 |
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+ | 2.9784 | 36.0135 | 370 | 6.2595 | 0.0 |
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+ | 3.0047 | 37.0135 | 380 | 6.5504 | 0.0 |
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+ | 2.98 | 38.0135 | 390 | 6.3898 | 0.0017 |
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+ | 2.9568 | 39.0135 | 400 | 6.8740 | 0.0017 |
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+ | 2.9418 | 40.0135 | 410 | 6.5854 | 0.0 |
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+ | 2.955 | 41.0135 | 420 | 6.5085 | 0.0052 |
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+ | 2.9689 | 42.0135 | 430 | 6.4343 | 0.0 |
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+ | 2.9494 | 43.0135 | 440 | 6.5746 | 0.0 |
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+ | 2.9363 | 44.0135 | 450 | 6.7996 | 0.0035 |
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+ | 2.9002 | 45.0135 | 460 | 7.1057 | 0.0035 |
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+ | 2.8776 | 46.0135 | 470 | 7.4000 | 0.0035 |
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+ | 2.8853 | 47.0135 | 480 | 6.9539 | 0.0017 |
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+ | 2.8618 | 48.0135 | 490 | 7.0917 | 0.0035 |
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+ | 2.8728 | 49.0135 | 500 | 7.4421 | 0.0017 |
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+ | 2.8888 | 50.0135 | 510 | 7.1914 | 0.0052 |
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+ | 2.8824 | 51.0135 | 520 | 7.3226 | 0.0069 |
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+ | 2.8932 | 52.0135 | 530 | 7.3581 | 0.0 |
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+ | 2.8562 | 53.0135 | 540 | 7.3102 | 0.0017 |
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+ | 2.8651 | 54.0135 | 550 | 7.2675 | 0.0035 |
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+ | 2.8898 | 55.0135 | 560 | 7.5446 | 0.0017 |
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+ | 2.8931 | 56.0135 | 570 | 7.2915 | 0.0 |
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+ | 2.8864 | 57.0135 | 580 | 7.2397 | 0.0017 |
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+ | 2.8683 | 58.0135 | 590 | 6.9988 | 0.0017 |
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+ | 2.8213 | 59.0135 | 600 | 7.4490 | 0.0052 |
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+ | 2.8319 | 60.0135 | 610 | 7.5569 | 0.0017 |
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+ | 2.8237 | 61.0135 | 620 | 7.5322 | 0.0017 |
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+ | 2.8057 | 62.0135 | 630 | 7.6815 | 0.0122 |
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+ | 2.8047 | 63.0135 | 640 | 7.3165 | 0.0 |
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+ | 2.8277 | 64.0135 | 650 | 7.4256 | 0.0069 |
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+ | 2.8202 | 65.0135 | 660 | 7.6688 | 0.0035 |
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+ | 2.772 | 66.0135 | 670 | 7.5628 | 0.0052 |
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+ | 2.7749 | 67.0135 | 680 | 7.7103 | 0.0052 |
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+ | 2.7442 | 68.0135 | 690 | 7.8151 | 0.0052 |
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+ | 2.7715 | 69.0135 | 700 | 7.8429 | 0.0052 |
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+ | 2.7593 | 70.0135 | 710 | 7.8079 | 0.0052 |
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+ | 2.7334 | 71.0135 | 720 | 7.8237 | 0.0052 |
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+ | 2.7392 | 72.0135 | 730 | 7.9085 | 0.0052 |
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+ | 2.753 | 73.0135 | 740 | 7.8889 | 0.0052 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.42.3
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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