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README.md ADDED
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+ ---
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+ library_name: transformers
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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: videomae-base-finetuned-kinetics-0408_final_5sec_org_ab7_val_as123
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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-kinetics-0408_final_5sec_org_ab7_val_as123
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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: 0.3219
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+ - Accuracy: 0.9225
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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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.05
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+ - training_steps: 65800
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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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+ | 0.537 | 0.0100 | 659 | 0.3567 | 0.8740 |
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+ | 0.0105 | 1.0100 | 1318 | 0.2819 | 0.9139 |
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+ | 0.0039 | 2.0100 | 1977 | 0.3886 | 0.8858 |
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+ | 0.0023 | 3.0100 | 2636 | 0.7164 | 0.8169 |
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+ | 0.0222 | 4.0100 | 3295 | 0.2866 | 0.9264 |
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+ | 0.0076 | 5.0100 | 3954 | 0.4126 | 0.9006 |
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+ | 1.008 | 6.0100 | 4613 | 0.3480 | 0.9006 |
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+ | 0.2086 | 7.0100 | 5272 | 0.2673 | 0.9311 |
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+ | 0.4466 | 8.0100 | 5931 | 0.3282 | 0.9264 |
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+ | 0.0067 | 9.0100 | 6590 | 0.3301 | 0.9116 |
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+ | 1.3353 | 10.0100 | 7249 | 0.5289 | 0.8654 |
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+ | 0.0003 | 11.0100 | 7908 | 0.6538 | 0.8732 |
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+ | 0.0003 | 12.0100 | 8567 | 0.3669 | 0.9241 |
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+ | 0.0184 | 13.0100 | 9226 | 0.3609 | 0.9171 |
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+ | 0.0002 | 14.0100 | 9885 | 0.5037 | 0.8975 |
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+ | 0.0001 | 15.0100 | 10544 | 0.4052 | 0.9202 |
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+ | 0.0077 | 16.0100 | 11203 | 0.5142 | 0.9014 |
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+ | 0.0001 | 17.0100 | 11862 | 0.3801 | 0.9241 |
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+ | 0.0092 | 18.0100 | 12521 | 0.5826 | 0.9030 |
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+ | 0.0012 | 19.0100 | 13180 | 0.4868 | 0.9155 |
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+ | 0.0043 | 20.0100 | 13839 | 0.4497 | 0.9186 |
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+ | 0.0001 | 21.0100 | 14498 | 0.7081 | 0.8858 |
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+ | 0.0 | 22.0100 | 15157 | 0.8394 | 0.8725 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.48.0
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
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