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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: 2.1806 |
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- Accuracy: 0.4883 |
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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: 32 |
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- eval_batch_size: 32 |
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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: 960 |
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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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| 4.2427 | 0.0323 | 31 | 4.2265 | 0.0033 | |
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| 4.2321 | 1.0323 | 62 | 4.2235 | 0.0100 | |
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| 4.24 | 2.0323 | 93 | 4.2282 | 0.0100 | |
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| 4.2445 | 3.0323 | 124 | 4.2250 | 0.0067 | |
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| 4.2327 | 4.0323 | 155 | 4.2244 | 0.0100 | |
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| 4.2104 | 5.0323 | 186 | 4.2100 | 0.0201 | |
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| 4.2374 | 6.0323 | 217 | 4.2022 | 0.0067 | |
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| 4.1597 | 7.0323 | 248 | 4.1188 | 0.0301 | |
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| 4.0522 | 8.0323 | 279 | 3.9351 | 0.0702 | |
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| 3.768 | 9.0323 | 310 | 3.6800 | 0.1070 | |
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| 3.5147 | 10.0323 | 341 | 3.5416 | 0.1104 | |
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| 3.2878 | 11.0323 | 372 | 3.7074 | 0.0702 | |
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| 2.9491 | 12.0323 | 403 | 3.3954 | 0.1070 | |
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| 2.806 | 13.0323 | 434 | 3.2552 | 0.1706 | |
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| 2.4568 | 14.0323 | 465 | 3.0654 | 0.2040 | |
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| 2.3102 | 15.0323 | 496 | 2.7440 | 0.3010 | |
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| 2.2079 | 16.0323 | 527 | 2.6789 | 0.3144 | |
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| 1.9638 | 17.0323 | 558 | 2.5920 | 0.3679 | |
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| 1.7914 | 18.0323 | 589 | 2.6152 | 0.3378 | |
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| 1.6925 | 19.0323 | 620 | 2.5971 | 0.3445 | |
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| 1.5124 | 20.0323 | 651 | 2.5767 | 0.3478 | |
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| 1.4834 | 21.0323 | 682 | 2.4439 | 0.3880 | |
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| 1.4565 | 22.0323 | 713 | 2.4057 | 0.3846 | |
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| 1.279 | 23.0323 | 744 | 2.5501 | 0.3545 | |
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| 1.1477 | 24.0323 | 775 | 2.3247 | 0.4482 | |
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| 1.2573 | 25.0323 | 806 | 2.1776 | 0.4883 | |
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| 1.0825 | 26.0323 | 837 | 2.1443 | 0.4783 | |
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| 1.2121 | 27.0323 | 868 | 2.1490 | 0.4783 | |
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| 1.0887 | 28.0323 | 899 | 2.1516 | 0.4716 | |
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| 1.1127 | 29.0323 | 930 | 2.1051 | 0.4883 | |
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| 0.9905 | 30.0312 | 960 | 2.1170 | 0.4816 | |
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### Framework versions |
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- Transformers 4.48.0 |
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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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