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  2. model.safetensors +1 -1
README.md ADDED
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+ ---
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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: finetuned-Accident-MultipleLabels-Video-subset-v2-new1
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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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+ # finetuned-Accident-MultipleLabels-Video-subset-v2-new1
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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: 1.9442
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+ - Accuracy: 0.2969
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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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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 32
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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: 20
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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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+ | No log | 0.1 | 2 | 1.8807 | 0.2031 |
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+ | No log | 1.1 | 4 | 1.8070 | 0.2812 |
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+ | No log | 2.1 | 6 | 1.8501 | 0.25 |
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+ | No log | 3.1 | 8 | 1.9253 | 0.2812 |
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+ | 1.6852 | 4.1 | 10 | 1.9988 | 0.2656 |
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+ | 1.6852 | 5.1 | 12 | 2.0073 | 0.2812 |
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+ | 1.6852 | 6.1 | 14 | 1.9848 | 0.2812 |
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+ | 1.6852 | 7.1 | 16 | 1.9575 | 0.2812 |
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+ | 1.6852 | 8.1 | 18 | 1.9472 | 0.2969 |
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+ | 1.4101 | 9.1 | 20 | 1.9442 | 0.2969 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.2.0.dev20231202+cu121
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
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