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README.md
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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-ucf101-epoch20
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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-epoch20
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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: 1.8347
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- Accuracy: 0.7704
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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: 2
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- eval_batch_size: 2
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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: 79120
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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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| 1.9278 | 0.05 | 3956 | 2.7016 | 0.3483 |
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| 0.6674 | 1.05 | 7912 | 1.5344 | 0.5915 |
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| 0.7501 | 2.05 | 11868 | 1.5602 | 0.6477 |
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| 0.3266 | 3.05 | 15824 | 1.6153 | 0.6807 |
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| 0.6674 | 4.05 | 19780 | 1.5007 | 0.7147 |
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| 0.0025 | 5.05 | 23736 | 1.5732 | 0.7065 |
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| 0.4971 | 6.05 | 27692 | 1.7131 | 0.7176 |
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| 0.0001 | 7.05 | 31648 | 1.5947 | 0.7482 |
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| 0.0003 | 8.05 | 35604 | 2.0551 | 0.6958 |
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| 0.2192 | 9.05 | 39560 | 1.7950 | 0.7356 |
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| 0.1505 | 10.05 | 43516 | 1.9480 | 0.7160 |
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| 0.0 | 11.05 | 47472 | 1.5406 | 0.7573 |
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| 0.0016 | 12.05 | 51428 | 1.9811 | 0.7207 |
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| 0.0005 | 13.05 | 55384 | 1.8196 | 0.7385 |
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| 0.0 | 14.05 | 59340 | 1.8393 | 0.7520 |
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| 0.0 | 15.05 | 63296 | 1.6738 | 0.7667 |
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| 0.0 | 16.05 | 67252 | 1.7355 | 0.7594 |
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| 0.0416 | 17.05 | 71208 | 1.7013 | 0.7638 |
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| 0.0 | 18.05 | 75164 | 1.6373 | 0.7709 |
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| 0.0 | 19.05 | 79120 | 1.5901 | 0.7763 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 2.0.1+cu117
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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