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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
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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
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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: 0.5590
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- Accuracy: 0.8641
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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: 8
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- eval_batch_size: 8
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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: 135
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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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| 0.7163 | 0.21 | 28 | 0.6078 | 0.8098 |
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| 0.7383 | 1.21 | 56 | 0.6975 | 0.4728 |
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| 0.6853 | 2.21 | 84 | 0.6637 | 0.6957 |
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| 0.7065 | 3.21 | 112 | 0.5590 | 0.8641 |
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| 0.6673 | 4.17 | 135 | 0.5766 | 0.8587 |
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### Framework versions
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- Transformers 4.26.0
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- Pytorch 1.13.1+cu116
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- Datasets 2.9.0
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- Tokenizers 0.13.2
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