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--- |
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license: cc-by-nc-4.0 |
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base_model: MCG-NJU/videomae-large |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: videomae-large_14class_UCFCrime |
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results: [] |
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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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# videomae-large_14class_UCFCrime |
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This model is a fine-tuned version of [MCG-NJU/videomae-large](https://huggingface.co./MCG-NJU/videomae-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- eval_loss: 2.1336 |
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- eval_confusion_matrix: {'confusion_matrix': array([[ 5, 6, 0, 11, 5, 1, 17, 1, 0, 0, 0, 6, 0, |
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0], |
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[ 25, 76, 0, 9, 53, 0, 36, 1, 24, 1, 0, 13, 5, |
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0], |
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[ 0, 0, 31, 0, 2, 0, 0, 0, 0, 0, 0, 0, 9, |
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7], |
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[ 11, 21, 0, 52, 3, 0, 40, 2, 1, 1, 0, 0, 19, |
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1], |
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[ 21, 9, 0, 1, 113, 0, 21, 2, 0, 30, 0, 1, 12, |
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43], |
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[ 1, 2, 13, 0, 0, 39, 1, 0, 0, 1, 0, 0, 12, |
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1], |
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[ 3, 15, 1, 23, 8, 0, 58, 0, 0, 6, 0, 23, 1, |
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4], |
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[ 0, 0, 0, 0, 0, 0, 0, 430, 0, 0, 0, 0, 0, |
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0], |
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[ 3, 11, 1, 2, 1, 2, 3, 0, 25, 3, 0, 4, 7, |
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0], |
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[ 0, 19, 0, 9, 17, 0, 18, 57, 0, 22, 0, 56, 0, |
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0], |
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[ 0, 11, 0, 6, 9, 0, 3, 3, 2, 0, 5, 3, 24, |
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0], |
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[ 0, 5, 0, 0, 0, 0, 5, 11, 0, 9, 0, 40, 0, |
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0], |
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[ 0, 40, 2, 19, 9, 0, 9, 44, 3, 0, 1, 30, 120, |
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11], |
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[ 0, 4, 1, 12, 2, 1, 0, 0, 0, 7, 0, 11, 6, |
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68]])} |
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- eval_runtime: 888.8746 |
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- eval_samples_per_second: 2.459 |
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- eval_steps_per_second: 1.23 |
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- step: 0 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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: 2 |
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- eval_batch_size: 2 |
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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: 5560 |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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