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End of training

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  2. pytorch_model.bin +1 -1
README.md ADDED
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+ ---
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+ license: mit
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+ base_model: google/vivit-b-16x2-kinetics400
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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: vivit-b-16x2-kinetics400-UCF-Crime
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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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+ # vivit-b-16x2-kinetics400-UCF-Crime
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+
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+ This model is a fine-tuned version of [google/vivit-b-16x2-kinetics400](https://huggingface.co/google/vivit-b-16x2-kinetics400) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.9757
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+ - Accuracy: 0.6149
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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: 3132
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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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+ | 1.2072 | 0.06 | 196 | 1.6400 | 0.5518 |
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+ | 1.5513 | 1.06 | 392 | 1.4988 | 0.5634 |
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+ | 1.1038 | 2.06 | 588 | 1.5328 | 0.5861 |
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+ | 0.9462 | 3.06 | 784 | 1.3932 | 0.6178 |
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+ | 0.7387 | 4.06 | 980 | 1.5449 | 0.6060 |
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+ | 0.5085 | 5.06 | 1176 | 1.3075 | 0.6287 |
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+ | 0.4443 | 6.06 | 1372 | 1.6743 | 0.6001 |
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+ | 0.4695 | 7.06 | 1568 | 1.5287 | 0.6172 |
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+ | 0.4409 | 8.06 | 1764 | 1.7749 | 0.6089 |
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+ | 0.1158 | 9.06 | 1960 | 1.9027 | 0.6076 |
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+ | 0.1183 | 10.06 | 2156 | 1.9622 | 0.6085 |
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+ | 0.1322 | 11.06 | 2352 | 2.0872 | 0.6152 |
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+ | 0.1881 | 12.06 | 2548 | 2.0095 | 0.6094 |
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+ | 0.0932 | 13.06 | 2744 | 1.9398 | 0.6232 |
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+ | 0.0303 | 14.06 | 2940 | 1.9994 | 0.6134 |
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+ | 0.0513 | 15.06 | 3132 | 1.9757 | 0.6149 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.2
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+ - Pytorch 1.10.0+cu113
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+ - Datasets 2.14.5
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+ - Tokenizers 0.13.3
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