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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-cart-activity-v0
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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-cart-activity-v0
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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: 0.2626
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- Accuracy: 0.9101
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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: 16
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- eval_batch_size: 16
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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: 1272
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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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| 0.4774 | 0.125 | 159 | 0.5977 | 0.7471 |
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| 0.2843 | 1.125 | 318 | 0.3505 | 0.8835 |
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| 0.2384 | 2.125 | 477 | 0.3886 | 0.8586 |
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| 0.2976 | 3.125 | 636 | 0.3410 | 0.8852 |
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| 0.2244 | 4.125 | 795 | 0.3221 | 0.8802 |
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| 0.2358 | 5.125 | 954 | 0.2995 | 0.8935 |
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| 0.2745 | 6.125 | 1113 | 0.2763 | 0.9052 |
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| 0.089 | 7.125 | 1272 | 0.2628 | 0.9101 |
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### Framework versions
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- Transformers 4.47.1
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- Pytorch 2.5.1+cu124
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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