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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-SingleLabel-Final-v2
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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-SingleLabel-Final-v2
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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: 1.2327
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+ - Accuracy: 0.5588
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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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+ - distributed_type: multi-GPU
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+ - num_devices: 2
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+ - total_train_batch_size: 16
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+ - total_eval_batch_size: 16
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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: 50
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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 | 0.08 | 4 | 1.8602 | 0.1304 |
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+ | No log | 1.08 | 8 | 1.6211 | 0.4783 |
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+ | 1.7588 | 2.08 | 12 | 1.4450 | 0.5652 |
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+ | 1.7588 | 3.08 | 16 | 1.2476 | 0.6087 |
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+ | 1.0616 | 4.08 | 20 | 1.1461 | 0.6087 |
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+ | 1.0616 | 5.08 | 24 | 1.0131 | 0.5217 |
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+ | 1.0616 | 6.08 | 28 | 0.9023 | 0.6087 |
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+ | 0.9537 | 7.08 | 32 | 0.9932 | 0.6087 |
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+ | 0.9537 | 8.08 | 36 | 0.9547 | 0.6087 |
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+ | 0.7395 | 9.08 | 40 | 1.0174 | 0.6087 |
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+ | 0.7395 | 10.08 | 44 | 0.9636 | 0.6087 |
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+ | 0.7395 | 11.08 | 48 | 0.9022 | 0.5652 |
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+ | 0.7531 | 12.04 | 50 | 0.9311 | 0.5652 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0
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+ - Pytorch 2.1.0
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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