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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-new3 |
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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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# finetuned-Accident-MultipleLabels-Video-subset-v2-new3 |
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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: 1.7434 |
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- Accuracy: 0.3333 |
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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: 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: 35 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 0.06 | 2 | 1.9011 | 0.1719 | |
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| No log | 1.06 | 4 | 1.8469 | 0.3281 | |
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| No log | 2.06 | 6 | 1.8533 | 0.3281 | |
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| No log | 3.06 | 8 | 1.9122 | 0.3281 | |
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| 1.6429 | 4.06 | 10 | 1.9870 | 0.3125 | |
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| 1.6429 | 5.06 | 12 | 1.9921 | 0.2969 | |
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| 1.6429 | 6.06 | 14 | 1.9683 | 0.3125 | |
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| 1.6429 | 7.06 | 16 | 1.9313 | 0.3125 | |
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| 1.6429 | 8.06 | 18 | 1.9203 | 0.3125 | |
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| 1.4144 | 9.06 | 20 | 1.9251 | 0.3125 | |
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| 1.4144 | 10.06 | 22 | 1.9316 | 0.2969 | |
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| 1.4144 | 11.06 | 24 | 1.9455 | 0.2969 | |
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| 1.4144 | 12.06 | 26 | 1.9723 | 0.2969 | |
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| 1.4144 | 13.06 | 28 | 1.9897 | 0.2969 | |
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| 1.3307 | 14.06 | 30 | 2.0000 | 0.2969 | |
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| 1.3307 | 15.06 | 32 | 2.0063 | 0.2969 | |
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| 1.3307 | 16.06 | 34 | 2.0072 | 0.2969 | |
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| 1.3307 | 17.03 | 35 | 2.0082 | 0.2969 | |
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### Framework versions |
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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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