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anirudhmu
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videomae-base-finetuned-soccer-action-recognitionx4

Video Classification
Transformers
TensorBoard
Safetensors
videomae
Generated from Trainer
Inference Endpoints
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  1. README.md +102 -0
  2. model.safetensors +1 -1
  3. runs/Nov15_22-20-49_f3214920728c/events.out.tfevents.1700098142.f3214920728c.2853.1 +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: 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-recognitionx4
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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-recognitionx4
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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: 0.1327
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+ - Accuracy: 0.9648
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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: 2e-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: 1125
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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 | 0.02 | 28 | 1.3255 | 0.3782 |
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+ | No log | 1.02 | 56 | 0.9903 | 0.5751 |
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+ | 1.1078 | 2.02 | 84 | 0.4648 | 0.8238 |
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+ | 1.1078 | 3.03 | 113 | 0.4075 | 0.8342 |
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+ | 1.1078 | 4.02 | 141 | 0.2301 | 0.9275 |
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+ | 0.2591 | 5.02 | 169 | 0.4090 | 0.8549 |
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+ | 0.2591 | 6.02 | 197 | 0.1527 | 0.9482 |
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+ | 0.2591 | 7.03 | 226 | 0.1413 | 0.9585 |
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+ | 0.111 | 8.02 | 254 | 0.1386 | 0.9637 |
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+ | 0.111 | 9.02 | 282 | 0.1674 | 0.9430 |
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+ | 0.111 | 10.02 | 310 | 0.1010 | 0.9741 |
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+ | 0.0509 | 11.03 | 339 | 0.1586 | 0.9637 |
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+ | 0.0509 | 12.02 | 367 | 0.2696 | 0.8860 |
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+ | 0.0509 | 13.02 | 395 | 0.3005 | 0.9171 |
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+ | 0.023 | 14.02 | 423 | 0.1001 | 0.9741 |
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+ | 0.023 | 15.03 | 452 | 0.1961 | 0.9482 |
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+ | 0.0354 | 16.02 | 480 | 0.2596 | 0.9223 |
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+ | 0.0354 | 17.02 | 508 | 0.1006 | 0.9689 |
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+ | 0.0354 | 18.02 | 536 | 0.0947 | 0.9793 |
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+ | 0.0141 | 19.03 | 565 | 0.0831 | 0.9793 |
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+ | 0.0141 | 20.02 | 593 | 0.0685 | 0.9793 |
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+ | 0.0141 | 21.02 | 621 | 0.0978 | 0.9689 |
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+ | 0.0168 | 22.02 | 649 | 0.0812 | 0.9793 |
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+ | 0.0168 | 23.03 | 678 | 0.0782 | 0.9793 |
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+ | 0.0168 | 24.02 | 706 | 0.2624 | 0.9275 |
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+ | 0.0029 | 25.02 | 734 | 0.1806 | 0.9534 |
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+ | 0.0029 | 26.02 | 762 | 0.2123 | 0.9585 |
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+ | 0.0029 | 27.03 | 791 | 0.2010 | 0.9482 |
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+ | 0.0048 | 28.02 | 819 | 0.1259 | 0.9689 |
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+ | 0.0048 | 29.02 | 847 | 0.2145 | 0.9430 |
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+ | 0.0048 | 30.02 | 875 | 0.2901 | 0.9223 |
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+ | 0.0042 | 31.03 | 904 | 0.0911 | 0.9793 |
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+ | 0.0042 | 32.02 | 932 | 0.0892 | 0.9741 |
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+ | 0.0024 | 33.02 | 960 | 0.0911 | 0.9845 |
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+ | 0.0024 | 34.02 | 988 | 0.0987 | 0.9741 |
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+ | 0.0024 | 35.03 | 1017 | 0.1446 | 0.9482 |
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+ | 0.0008 | 36.02 | 1045 | 0.1415 | 0.9482 |
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+ | 0.0008 | 37.02 | 1073 | 0.1435 | 0.9482 |
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+ | 0.0008 | 38.02 | 1101 | 0.1438 | 0.9482 |
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+ | 0.0008 | 39.02 | 1125 | 0.1371 | 0.9534 |
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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 2.1.0+cu118
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+ - Datasets 2.14.7
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+ - Tokenizers 0.15.0
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