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dmsrud/anomalous_behavior_video_cls_model

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  1. README.md +63 -0
  2. config.json +56 -0
  3. model.safetensors +3 -0
  4. training_args.bin +3 -0
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
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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: anomalous_behavior_video_cls_model
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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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+ # anomalous_behavior_video_cls_model
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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: 2.2999
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+ - Accuracy: 0.1573
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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: 2
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+ - eval_batch_size: 2
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 0.1
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+ - training_steps: 267
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+ - mixed_precision_training: Native AMP
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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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+ | 2.122 | 1.0 | 267 | 2.2999 | 0.1573 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.56.1
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+ - Pytorch 2.8.0+cu126
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+ - Datasets 4.0.0
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+ - Tokenizers 0.22.0
config.json ADDED
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+ {
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+ "architectures": [
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+ "VideoMAEForVideoClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.0,
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+ "decoder_hidden_size": 384,
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+ "decoder_intermediate_size": 1536,
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+ "decoder_num_attention_heads": 6,
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+ "decoder_num_hidden_layers": 4,
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+ "dtype": "float32",
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.0,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "assult",
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+ "1": "datefight",
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+ "2": "robbery",
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+ "3": "burglary",
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+ "4": "trespass",
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+ "5": "wander",
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+ "6": "vandalism",
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+ "7": "fight",
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+ "8": "dump",
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+ "9": "swoon",
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+ "10": "kidnap"
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+ },
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+ "image_size": 224,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "label2id": {
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+ "assult": 0,
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+ "burglary": 3,
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+ "datefight": 1,
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+ "dump": 8,
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+ "fight": 7,
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+ "kidnap": 10,
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+ "robbery": 2,
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+ "swoon": 9,
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+ "trespass": 4,
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+ "vandalism": 6,
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+ "wander": 5
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "model_type": "videomae",
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+ "norm_pix_loss": true,
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+ "num_attention_heads": 12,
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+ "num_channels": 3,
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+ "num_frames": 16,
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+ "num_hidden_layers": 12,
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+ "patch_size": 16,
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+ "problem_type": "single_label_classification",
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+ "qkv_bias": true,
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+ "transformers_version": "4.56.1",
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+ "tubelet_size": 2,
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+ "use_mean_pooling": false
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+ }
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