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---
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license: cc-by-nc-4.0
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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-basketball-subset-20epochs
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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-basketball-subset-20epochs
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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: 2.8785
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- Accuracy: 0.1972
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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: 1
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- eval_batch_size: 1
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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: 4060
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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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| 1.2525 | 0.05 | 200 | 0.7720 | 0.52 |
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| 0.8649 | 1.05 | 400 | 0.7721 | 0.48 |
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| 1.0703 | 2.05 | 600 | 1.3605 | 0.52 |
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| 0.606 | 3.05 | 800 | 1.0668 | 0.6 |
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| 2.0221 | 4.05 | 1000 | 1.1741 | 0.56 |
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| 1.2916 | 5.05 | 1200 | 1.4747 | 0.52 |
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| 1.4861 | 6.05 | 1400 | 1.1454 | 0.6 |
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| 1.3012 | 7.05 | 1600 | 1.6105 | 0.56 |
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| 1.3327 | 8.05 | 1800 | 1.2343 | 0.52 |
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| 2.077 | 9.05 | 2000 | 1.3243 | 0.6 |
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| 1.2349 | 10.05 | 2200 | 1.2044 | 0.6 |
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| 1.005 | 11.05 | 2400 | 1.6417 | 0.52 |
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| 1.1622 | 12.05 | 2600 | 1.3058 | 0.56 |
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| 0.8031 | 13.05 | 2800 | 0.6776 | 0.48 |
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| 0.8588 | 14.05 | 3000 | 1.1644 | 0.64 |
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| 0.8451 | 15.05 | 3200 | 0.8491 | 0.64 |
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| 1.1336 | 16.05 | 3400 | 1.0237 | 0.6 |
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| 1.5719 | 17.05 | 3600 | 1.0391 | 0.64 |
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| 0.4892 | 18.05 | 3800 | 0.9995 | 0.64 |
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| 1.2092 | 19.05 | 4000 | 0.9802 | 0.56 |
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| 0.9784 | 20.01 | 4060 | 0.9771 | 0.56 |
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### Framework versions
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- Transformers 4.28.1
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- Pytorch 2.0.0+cu118
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- Datasets 2.11.0
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- Tokenizers 0.13.3
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