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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-d2
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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-d2
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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: 2.4405
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- Accuracy: 0.2817
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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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- training_steps: 6650
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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 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 2.5533 | 0.1 | 665 | 2.5143 | 0.1135 |
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| 2.5289 | 1.1 | 1330 | 2.5014 | 0.1412 |
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| 2.037 | 2.1 | 1995 | 2.4798 | 0.1724 |
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| 2.5935 | 3.1 | 2660 | 2.4935 | 0.1804 |
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| 1.779 | 4.1 | 3325 | 2.3578 | 0.2324 |
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| 1.8988 | 5.1 | 3990 | 2.3659 | 0.2546 |
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| 2.2268 | 6.1 | 4655 | 2.3632 | 0.2402 |
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| 1.5192 | 7.1 | 5320 | 2.4079 | 0.2452 |
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| 2.0327 | 8.1 | 5985 | 2.4804 | 0.2773 |
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| 1.5885 | 9.1 | 6650 | 2.4405 | 0.2817 |
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### Framework versions
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- Transformers 4.46.2
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- Pytorch 2.5.1+cu124
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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