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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: videomae-base-finetuned-ucf101-subset |
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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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# videomae-base-finetuned-ucf101-subset |
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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: 0.3320 |
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- Accuracy: 0.9290 |
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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: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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- optimizer: Use 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: 600 |
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- mixed_precision_training: Native AMP |
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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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| 2.3375 | 0.0617 | 37 | 2.1297 | 0.3 | |
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| 1.7263 | 1.0625 | 75 | 1.4907 | 0.4714 | |
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| 0.675 | 2.0617 | 112 | 0.6070 | 0.8714 | |
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| 0.3702 | 3.0625 | 150 | 0.4089 | 0.8571 | |
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| 0.205 | 4.0617 | 187 | 0.4285 | 0.8286 | |
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| 0.3209 | 5.0625 | 225 | 0.2749 | 0.8714 | |
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| 0.1253 | 6.0617 | 262 | 0.0571 | 0.9857 | |
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| 0.1052 | 7.0625 | 300 | 0.2550 | 0.9429 | |
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| 0.1586 | 8.0617 | 337 | 0.1588 | 0.9429 | |
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| 0.0498 | 9.0625 | 375 | 0.0736 | 0.9857 | |
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| 0.0958 | 10.0617 | 412 | 0.0911 | 0.9571 | |
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| 0.1095 | 11.0625 | 450 | 0.0448 | 0.9857 | |
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| 0.0065 | 12.0617 | 487 | 0.0734 | 0.9857 | |
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| 0.0019 | 13.0625 | 525 | 0.0603 | 0.9857 | |
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| 0.0018 | 14.0617 | 562 | 0.0607 | 0.9857 | |
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| 0.0018 | 15.0625 | 600 | 0.0634 | 0.9857 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 3.2.0 |
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- Tokenizers 0.20.3 |
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