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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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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: videomae-base-finetuned-numbers-augmented2 |
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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-numbers-augmented2 |
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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: 0.1392 |
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- Accuracy: 0.9681 |
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- F1: 0.9680 |
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- Precision: 0.9692 |
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- Recall: 0.9678 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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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: 6756 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 1.3906 | 0.0833 | 563 | 1.2362 | 0.5628 | 0.5561 | 0.6171 | 0.5623 | |
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| 0.7242 | 1.0833 | 1126 | 0.8677 | 0.6867 | 0.6787 | 0.7247 | 0.6847 | |
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| 0.5625 | 2.0833 | 1689 | 0.6211 | 0.7883 | 0.7865 | 0.8163 | 0.7871 | |
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| 0.5111 | 3.0833 | 2252 | 0.4169 | 0.8623 | 0.8621 | 0.8814 | 0.8631 | |
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| 0.1224 | 4.0833 | 2815 | 0.2908 | 0.9036 | 0.9030 | 0.9077 | 0.9038 | |
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| 0.0561 | 5.0833 | 3378 | 0.2836 | 0.9208 | 0.9207 | 0.9252 | 0.9210 | |
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| 0.0028 | 6.0833 | 3941 | 0.2256 | 0.9466 | 0.9470 | 0.9488 | 0.9471 | |
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| 0.0009 | 7.0833 | 4504 | 0.1670 | 0.9673 | 0.9676 | 0.9702 | 0.9665 | |
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| 0.0336 | 8.0833 | 5067 | 0.1362 | 0.9656 | 0.9656 | 0.9674 | 0.9650 | |
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| 0.0004 | 9.0833 | 5630 | 0.1192 | 0.9776 | 0.9778 | 0.9793 | 0.9771 | |
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| 0.0004 | 10.0833 | 6193 | 0.1204 | 0.9725 | 0.9725 | 0.9745 | 0.9719 | |
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| 0.0003 | 11.0833 | 6756 | 0.1268 | 0.9725 | 0.9723 | 0.9738 | 0.9719 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.19.1 |
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