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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 |
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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 |
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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: 0.3433 |
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- Accuracy: 0.8222 |
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- F1: 0.8015 |
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- Precision: 0.8762 |
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- Recall: 0.8182 |
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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: 176 |
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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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| 0.7592 | 0.25 | 44 | 0.6378 | 0.8462 | 0.8479 | 0.8758 | 0.8561 | |
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| 0.296 | 1.25 | 88 | 0.3027 | 0.8974 | 0.8805 | 0.9091 | 0.8864 | |
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| 0.2144 | 2.25 | 132 | 0.1289 | 0.9487 | 0.9377 | 0.9545 | 0.9394 | |
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| 0.1331 | 3.25 | 176 | 0.0958 | 0.9744 | 0.9688 | 0.9773 | 0.9697 | |
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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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