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Intoxicated_Classification

Video Classification
Transformers
TensorBoard
Safetensors
videomae
Generated from Trainer
Model card Files
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Metrics Community
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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
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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: Intoxicated_Classification
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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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+ # Intoxicated_Classification
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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: 1.7660
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+ - Accuracy: 0.6971
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+ - F1 Macro: 0.6962
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+ - F1 Weighted: 0.6990
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+ - Precision Macro: 0.7040
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+ - Precision Weighted: 0.7216
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+ - Recall Macro: 0.7094
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+ - Recall Weighted: 0.6971
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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 OptimizerNames.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: 0.1
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+ - training_steps: 6980
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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 | F1 Macro | F1 Weighted | Precision Macro | Precision Weighted | Recall Macro | Recall Weighted |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|:---------------:|:------------------:|:------------:|:---------------:|
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+ | 0.3101 | 0.1 | 698 | 1.1498 | 0.6133 | 0.6127 | 0.6100 | 0.6448 | 0.6663 | 0.6396 | 0.6133 |
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+ | 0.0223 | 1.1 | 1396 | 2.0621 | 0.6154 | 0.6114 | 0.6046 | 0.6727 | 0.6992 | 0.6528 | 0.6154 |
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+ | 0.071 | 2.1 | 2094 | 1.1017 | 0.6650 | 0.6649 | 0.6641 | 0.6905 | 0.7124 | 0.6884 | 0.6650 |
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+ | 0.1562 | 3.1 | 2792 | 0.9922 | 0.7803 | 0.7713 | 0.7792 | 0.7746 | 0.7791 | 0.7691 | 0.7803 |
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+ | 0.1505 | 4.1 | 3490 | 0.6705 | 0.8203 | 0.8157 | 0.8208 | 0.8143 | 0.8217 | 0.8176 | 0.8203 |
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+ | 0.0634 | 5.1 | 4188 | 2.0951 | 0.6155 | 0.6122 | 0.6059 | 0.6687 | 0.6945 | 0.6515 | 0.6155 |
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+ | 0.0002 | 6.1 | 4886 | 2.2097 | 0.6473 | 0.6472 | 0.6483 | 0.6627 | 0.6818 | 0.6645 | 0.6473 |
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+ | 0.0366 | 7.1 | 5584 | 1.7946 | 0.6842 | 0.6837 | 0.6858 | 0.6947 | 0.7133 | 0.6988 | 0.6842 |
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+ | 0.0002 | 8.1 | 6282 | 1.8526 | 0.6838 | 0.6832 | 0.6856 | 0.6926 | 0.7107 | 0.6972 | 0.6838 |
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+ | 0.0004 | 9.1 | 6980 | 1.7660 | 0.6971 | 0.6962 | 0.6990 | 0.7040 | 0.7216 | 0.7094 | 0.6971 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.51.3
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+ - Pytorch 2.6.0+cu124
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+ - Datasets 3.5.1
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+ - Tokenizers 0.21.1
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