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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-finetuned-ucf101-subset
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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-ucf101-subset
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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: 0.4435
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- Accuracy: 0.8452
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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: 148
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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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| 2.3498 | 0.1284 | 19 | 2.0894 | 0.2143 |
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| 1.9304 | 1.1284 | 38 | 1.5131 | 0.4857 |
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| 1.099 | 2.1284 | 57 | 0.8322 | 0.6857 |
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| 0.4725 | 3.1284 | 76 | 0.5528 | 0.7714 |
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| 0.3629 | 4.1284 | 95 | 0.3822 | 0.8571 |
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| 0.196 | 5.1284 | 114 | 0.3011 | 0.9143 |
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| 0.1357 | 6.1284 | 133 | 0.2539 | 0.9143 |
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| 0.0847 | 7.1014 | 148 | 0.1923 | 0.9429 |
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### Framework versions
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- Transformers 4.48.1
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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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