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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-ucf_crime2 |
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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-ucf_crime2 |
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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: 1.8463 |
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- Accuracy: 0.5200 |
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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: 2700 |
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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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| 0.475 | 0.05 | 135 | 0.9935 | 0.6004 | |
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| 1.44 | 1.05 | 270 | 1.4196 | 0.4274 | |
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| 1.1084 | 2.05 | 405 | 0.9135 | 0.6737 | |
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| 0.8732 | 3.05 | 540 | 1.1984 | 0.5479 | |
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| 1.4184 | 4.05 | 675 | 1.3373 | 0.4926 | |
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| 1.1355 | 5.05 | 810 | 0.9888 | 0.6148 | |
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| 0.4522 | 6.05 | 945 | 1.0745 | 0.5694 | |
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| 0.7754 | 7.05 | 1080 | 1.5848 | 0.5330 | |
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| 1.1235 | 8.05 | 1215 | 1.3688 | 0.5753 | |
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| 1.611 | 9.05 | 1350 | 0.6958 | 0.7694 | |
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| 0.5714 | 10.05 | 1485 | 0.8027 | 0.7542 | |
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| 0.716 | 11.05 | 1620 | 1.3503 | 0.6782 | |
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| 0.6642 | 12.05 | 1755 | 1.0798 | 0.6957 | |
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| 0.8451 | 13.05 | 1890 | 1.2328 | 0.7479 | |
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| 0.6157 | 14.05 | 2025 | 1.9403 | 0.5762 | |
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| 0.3358 | 15.05 | 2160 | 1.3435 | 0.6939 | |
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| 0.5394 | 16.05 | 2295 | 1.2524 | 0.7056 | |
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| 0.3334 | 17.05 | 2430 | 1.1190 | 0.7645 | |
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| 0.3513 | 18.05 | 2565 | 1.2137 | 0.7461 | |
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| 0.2531 | 19.05 | 2700 | 1.2131 | 0.7362 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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