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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: working |
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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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# working |
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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: 4.6095 |
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- Accuracy: 0.0266 |
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- Top 1 Accuracy: 0.0266 |
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- Top 5 Accuracy: 0.0858 |
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- Top 10 Accuracy: 0.1420 |
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- Macro Precision: 0.0024 |
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- Macro Recall: 0.0173 |
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- Macro F1: 0.0039 |
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- Pearson Corr: 0.3016 |
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- Spearman Corr: 0.2739 |
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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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- gradient_accumulation_steps: 4 |
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- total_train_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: 900 |
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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 | Top 1 Accuracy | Top 5 Accuracy | Top 10 Accuracy | Macro Precision | Macro Recall | Macro F1 | Pearson Corr | Spearman Corr | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:--------------:|:--------------:|:---------------:|:---------------:|:------------:|:--------:|:------------:|:-------------:| |
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| 4.523 | 5.0542 | 500 | 4.6095 | 0.0266 | 0.0266 | 0.0858 | 0.1420 | 0.0024 | 0.0173 | 0.0039 | 0.3016 | 0.2739 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 1.11.0+cu102 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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