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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-base
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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-soccer-action-recognitionx
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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-soccer-action-recognitionx
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+
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+ This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2575
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+ - Accuracy: 0.9281
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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: 4
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+ - eval_batch_size: 4
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+ - seed: 42
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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 32
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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: 1376
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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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+ | No log | 0.03 | 43 | 1.8151 | 0.3661 |
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+ | 1.7589 | 1.03 | 86 | 0.9133 | 0.6915 |
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+ | 1.7589 | 2.03 | 129 | 0.5026 | 0.7966 |
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+ | 0.5494 | 3.03 | 172 | 0.3937 | 0.8678 |
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+ | 0.5494 | 4.03 | 215 | 0.3943 | 0.8678 |
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+ | 0.2747 | 5.03 | 258 | 0.3876 | 0.8678 |
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+ | 0.2747 | 6.03 | 301 | 0.2803 | 0.9085 |
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+ | 0.1731 | 7.03 | 345 | 0.2414 | 0.9119 |
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+ | 0.1731 | 8.03 | 388 | 0.2434 | 0.9288 |
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+ | 0.1165 | 9.03 | 431 | 0.1560 | 0.9458 |
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+ | 0.1165 | 10.03 | 474 | 0.1894 | 0.9254 |
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+ | 0.07 | 11.03 | 517 | 0.2401 | 0.9153 |
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+ | 0.0417 | 12.03 | 560 | 0.1883 | 0.9390 |
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+ | 0.0417 | 13.03 | 603 | 0.2589 | 0.9051 |
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+ | 0.0362 | 14.03 | 646 | 0.2125 | 0.9492 |
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+ | 0.0362 | 15.03 | 690 | 0.2228 | 0.9390 |
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+ | 0.0348 | 16.03 | 733 | 0.1797 | 0.9525 |
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+ | 0.0348 | 17.03 | 776 | 0.1728 | 0.9390 |
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+ | 0.0129 | 18.03 | 819 | 0.2253 | 0.9254 |
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+ | 0.0129 | 19.03 | 862 | 0.1983 | 0.9356 |
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+ | 0.0112 | 20.03 | 905 | 0.2821 | 0.9220 |
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+ | 0.0112 | 21.03 | 948 | 0.2527 | 0.9356 |
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+ | 0.0165 | 22.03 | 991 | 0.2598 | 0.9288 |
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+ | 0.0165 | 23.03 | 1035 | 0.2690 | 0.9288 |
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+ | 0.0056 | 24.03 | 1078 | 0.2817 | 0.9220 |
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+ | 0.0026 | 25.03 | 1121 | 0.2039 | 0.9424 |
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+ | 0.0026 | 26.03 | 1164 | 0.2164 | 0.9458 |
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+ | 0.0033 | 27.03 | 1207 | 0.2063 | 0.9424 |
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+ | 0.0033 | 28.03 | 1250 | 0.1836 | 0.9525 |
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+ | 0.0038 | 29.03 | 1293 | 0.1899 | 0.9458 |
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+ | 0.0038 | 30.03 | 1336 | 0.1815 | 0.9492 |
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+ | 0.0024 | 31.03 | 1376 | 0.1816 | 0.9525 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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