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README.md
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---
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library_name: transformers
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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: videomae-base-face
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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-face
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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: 1.8802
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- Accuracy: 0.6944
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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: 5
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- eval_batch_size: 5
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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: 1200
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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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| 1.6771 | 16.0033 | 100 | 1.5844 | 0.2222 |
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| 0.2052 | 33.0017 | 200 | 1.8833 | 0.4722 |
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| 0.6001 | 49.005 | 300 | 1.4486 | 0.6944 |
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| 0.3118 | 66.0033 | 400 | 0.1618 | 0.9722 |
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| 0.0046 | 83.0017 | 500 | 2.1274 | 0.6944 |
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| 0.0528 | 99.005 | 600 | 1.8246 | 0.7222 |
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| 0.0174 | 116.0033 | 700 | 1.9694 | 0.7222 |
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| 0.2597 | 133.0017 | 800 | 2.0549 | 0.6944 |
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| 0.0505 | 149.005 | 900 | 1.9087 | 0.7222 |
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| 0.0014 | 166.0033 | 1000 | 2.0244 | 0.6944 |
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| 0.0324 | 183.0017 | 1100 | 1.5456 | 0.75 |
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| 0.0011 | 199.005 | 1200 | 1.8802 | 0.6944 |
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### Framework versions
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- Transformers 4.45.0
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- Pytorch 2.4.1+cu118
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- Datasets 3.0.0
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- Tokenizers 0.20.0
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