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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-v3 |
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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-SingleLabel-Final-v3 |
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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: 0.7942 |
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- Accuracy: 0.6471 |
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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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- 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: 65 |
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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 | 4 | 1.8584 | 0.1739 | |
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| No log | 1.06 | 8 | 1.6548 | 0.3478 | |
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| 1.6685 | 2.06 | 12 | 1.4049 | 0.5217 | |
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| 1.6685 | 3.06 | 16 | 1.1540 | 0.6087 | |
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| 1.0202 | 4.06 | 20 | 1.1246 | 0.6087 | |
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| 1.0202 | 5.06 | 24 | 1.0258 | 0.4348 | |
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| 1.0202 | 6.06 | 28 | 0.9200 | 0.5217 | |
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| 0.9738 | 7.06 | 32 | 0.8942 | 0.6087 | |
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| 0.9738 | 8.06 | 36 | 0.8556 | 0.6087 | |
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| 0.7315 | 9.06 | 40 | 0.9506 | 0.6087 | |
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| 0.7315 | 10.06 | 44 | 0.9272 | 0.6087 | |
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| 0.7315 | 11.06 | 48 | 0.8048 | 0.5652 | |
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| 0.7004 | 12.06 | 52 | 0.8537 | 0.5217 | |
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| 0.7004 | 13.06 | 56 | 0.8058 | 0.6087 | |
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| 0.7426 | 14.06 | 60 | 1.0633 | 0.6957 | |
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| 0.7426 | 15.06 | 64 | 0.9449 | 0.6522 | |
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| 0.7426 | 16.02 | 65 | 0.8110 | 0.6522 | |
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### Framework versions |
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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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