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abduldattijo
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videomae-base-finetuned-ucf101-subset-V3KILLER

Video Classification
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videomae
Generated from Trainer
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  2. model.safetensors +1 -1
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  4. runs/Nov16_17-29-36_DESKTOP-T6E146I/events.out.tfevents.1700217743.DESKTOP-T6E146I.18100.1 +3 -0
README.md ADDED
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+ ---
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+ license: cc-by-nc-4.0
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+ base_model: abduldattijo/videomae-base-finetuned-ucf101-subset
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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-V3KILLER
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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-V3KILLER
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+
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+ This model is a fine-tuned version of [abduldattijo/videomae-base-finetuned-ucf101-subset](https://huggingface.co/abduldattijo/videomae-base-finetuned-ucf101-subset) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2181
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+ - Accuracy: 0.9615
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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: 8
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+ - eval_batch_size: 8
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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: 5960
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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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+ | 0.3447 | 0.03 | 150 | 0.1339 | 0.9579 |
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+ | 0.3161 | 1.03 | 300 | 0.1538 | 0.9465 |
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+ | 0.3386 | 2.03 | 450 | 0.3260 | 0.9019 |
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+ | 0.3572 | 3.03 | 600 | 0.1967 | 0.9311 |
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+ | 0.3699 | 4.03 | 750 | 0.1661 | 0.9505 |
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+ | 0.3125 | 5.03 | 900 | 0.3292 | 0.9205 |
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+ | 0.4785 | 6.03 | 1050 | 0.2029 | 0.9324 |
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+ | 0.3477 | 7.03 | 1200 | 0.1534 | 0.9385 |
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+ | 0.2909 | 8.03 | 1350 | 0.1265 | 0.9571 |
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+ | 0.2646 | 9.03 | 1500 | 0.1239 | 0.9586 |
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+ | 0.3339 | 10.03 | 1650 | 0.1341 | 0.9628 |
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+ | 0.0954 | 11.03 | 1800 | 0.1835 | 0.9423 |
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+ | 0.3861 | 12.03 | 1950 | 0.2241 | 0.9467 |
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+ | 0.248 | 13.03 | 2100 | 0.1258 | 0.9620 |
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+ | 0.2513 | 14.03 | 2250 | 0.2217 | 0.9357 |
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+ | 0.1133 | 15.03 | 2400 | 0.2129 | 0.9406 |
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+ | 0.1421 | 16.03 | 2550 | 0.3006 | 0.9264 |
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+ | 0.0248 | 17.03 | 2700 | 0.3868 | 0.9142 |
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+ | 0.0166 | 18.03 | 2850 | 0.2594 | 0.9518 |
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+ | 0.0874 | 19.03 | 3000 | 0.3652 | 0.9252 |
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+ | 0.0889 | 20.03 | 3150 | 0.2249 | 0.9533 |
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+ | 0.0804 | 21.03 | 3300 | 0.2027 | 0.9628 |
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+ | 0.0019 | 22.03 | 3450 | 0.4682 | 0.9212 |
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+ | 0.0405 | 23.03 | 3600 | 0.2425 | 0.9493 |
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+ | 0.0847 | 24.03 | 3750 | 0.2456 | 0.9558 |
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+ | 0.1656 | 25.03 | 3900 | 0.2623 | 0.9505 |
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+ | 0.1007 | 26.03 | 4050 | 0.2389 | 0.9484 |
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+ | 0.0616 | 27.03 | 4200 | 0.2529 | 0.9543 |
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+ | 0.0005 | 28.03 | 4350 | 0.1521 | 0.9732 |
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+ | 0.0006 | 29.03 | 4500 | 0.4115 | 0.9165 |
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+ | 0.0007 | 30.03 | 4650 | 0.4279 | 0.9220 |
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+ | 0.0004 | 31.03 | 4800 | 0.3572 | 0.9372 |
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+ | 0.0003 | 32.03 | 4950 | 0.3314 | 0.9419 |
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+ | 0.0002 | 33.03 | 5100 | 0.4008 | 0.9347 |
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+ | 0.0611 | 34.03 | 5250 | 0.4632 | 0.9239 |
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+ | 0.0003 | 35.03 | 5400 | 0.3756 | 0.9368 |
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+ | 0.0003 | 36.03 | 5550 | 0.3745 | 0.9429 |
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+ | 0.163 | 37.03 | 5700 | 0.3967 | 0.9383 |
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+ | 0.0059 | 38.03 | 5850 | 0.3808 | 0.9389 |
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+ | 0.0003 | 39.02 | 5960 | 0.3824 | 0.9395 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.1+cu118
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
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