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--- |
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library_name: transformers |
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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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model-index: |
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- name: student_videomobilevit_not_learning_RWF2000 |
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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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# student_videomobilevit_not_learning_RWF2000 |
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This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4668 |
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- Accuracy: 0.8531 |
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- F1: 0.8530 |
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- Precision: 0.8542 |
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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: 1e-05 |
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- train_batch_size: 20 |
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- eval_batch_size: 20 |
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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_steps: 180 |
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- training_steps: 1800 |
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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 | F1 | Precision | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:| |
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| 0.5117 | 2.02 | 180 | 0.4612 | 0.7844 | 0.7841 | 0.7857 | |
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| 0.3803 | 4.04 | 360 | 0.4049 | 0.8156 | 0.8150 | 0.8201 | |
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| 0.3181 | 7.02 | 540 | 0.4287 | 0.8 | 0.7989 | 0.8069 | |
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| 0.2548 | 9.04 | 720 | 0.4230 | 0.8094 | 0.8080 | 0.8184 | |
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| 0.2348 | 12.02 | 900 | 0.3655 | 0.85 | 0.85 | 0.85 | |
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| 0.1722 | 14.04 | 1080 | 0.3827 | 0.8594 | 0.8594 | 0.8595 | |
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| 0.1861 | 17.02 | 1260 | 0.4371 | 0.8562 | 0.8562 | 0.8571 | |
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| 0.1753 | 19.04 | 1440 | 0.4214 | 0.8438 | 0.8435 | 0.8457 | |
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| 0.1464 | 22.02 | 1620 | 0.5414 | 0.8438 | 0.8427 | 0.8531 | |
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| 0.1411 | 24.04 | 1800 | 0.4668 | 0.8531 | 0.8530 | 0.8542 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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