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--- |
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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-subset-0401 |
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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-subset-0401 |
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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: 0.6379 |
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- Accuracy: 0.7824 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 2775 |
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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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| 1.6048 | 0.02 | 56 | 1.6213 | 0.0829 | |
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| 1.5891 | 1.02 | 112 | 1.5230 | 0.2811 | |
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| 1.4797 | 2.02 | 168 | 1.6437 | 0.1982 | |
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| 1.3999 | 3.02 | 224 | 0.9263 | 0.7465 | |
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| 1.0917 | 4.02 | 280 | 1.2308 | 0.4931 | |
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| 1.238 | 5.02 | 336 | 0.9406 | 0.6590 | |
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| 1.1525 | 6.02 | 392 | 0.8809 | 0.7051 | |
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| 1.0806 | 7.02 | 448 | 1.0089 | 0.5945 | |
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| 0.8483 | 8.02 | 504 | 0.9700 | 0.5853 | |
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| 0.992 | 9.02 | 560 | 1.1880 | 0.4885 | |
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| 0.862 | 10.02 | 616 | 0.7174 | 0.7512 | |
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| 1.0694 | 11.02 | 672 | 0.8598 | 0.7143 | |
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| 0.8885 | 12.02 | 728 | 0.8290 | 0.7097 | |
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| 0.8965 | 13.02 | 784 | 0.8304 | 0.7143 | |
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| 0.7371 | 14.02 | 840 | 0.7009 | 0.7696 | |
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| 0.6872 | 15.02 | 896 | 0.6768 | 0.7926 | |
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| 0.6022 | 16.02 | 952 | 0.7513 | 0.7373 | |
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| 0.9308 | 17.02 | 1008 | 0.8055 | 0.7097 | |
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| 0.4456 | 18.02 | 1064 | 0.7876 | 0.6728 | |
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| 0.6802 | 19.02 | 1120 | 0.7224 | 0.7235 | |
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| 0.7154 | 20.02 | 1176 | 0.7434 | 0.7051 | |
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| 0.503 | 21.02 | 1232 | 0.8346 | 0.6959 | |
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| 0.7203 | 22.02 | 1288 | 0.9694 | 0.5991 | |
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| 0.6799 | 23.02 | 1344 | 0.6474 | 0.7696 | |
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| 0.5802 | 24.02 | 1400 | 0.9573 | 0.6359 | |
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| 0.7047 | 25.02 | 1456 | 0.9120 | 0.6959 | |
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| 0.6701 | 26.02 | 1512 | 1.1690 | 0.5853 | |
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| 0.5514 | 27.02 | 1568 | 0.9174 | 0.6866 | |
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| 0.538 | 28.02 | 1624 | 0.8543 | 0.6866 | |
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| 0.7226 | 29.02 | 1680 | 0.7774 | 0.7465 | |
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| 0.4459 | 30.02 | 1736 | 0.9135 | 0.6359 | |
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| 0.3905 | 31.02 | 1792 | 0.8586 | 0.6728 | |
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| 0.7071 | 32.02 | 1848 | 0.7919 | 0.7327 | |
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| 0.4983 | 33.02 | 1904 | 0.7507 | 0.7512 | |
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| 0.5654 | 34.02 | 1960 | 0.7679 | 0.7143 | |
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| 0.5569 | 35.02 | 2016 | 0.8438 | 0.7097 | |
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| 0.3998 | 36.02 | 2072 | 0.8691 | 0.7189 | |
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| 0.5341 | 37.02 | 2128 | 0.8056 | 0.7604 | |
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| 0.4024 | 38.02 | 2184 | 0.7071 | 0.7880 | |
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| 0.5011 | 39.02 | 2240 | 0.8827 | 0.7005 | |
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| 0.5857 | 40.02 | 2296 | 0.8525 | 0.7097 | |
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| 0.5619 | 41.02 | 2352 | 0.8228 | 0.7512 | |
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| 0.6052 | 42.02 | 2408 | 0.8320 | 0.7373 | |
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| 0.5124 | 43.02 | 2464 | 0.8776 | 0.7419 | |
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| 0.3323 | 44.02 | 2520 | 0.8515 | 0.7465 | |
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| 0.5684 | 45.02 | 2576 | 0.9309 | 0.7097 | |
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| 0.4406 | 46.02 | 2632 | 0.8826 | 0.7465 | |
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| 0.6164 | 47.02 | 2688 | 0.8994 | 0.6959 | |
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| 0.4549 | 48.02 | 2744 | 0.8700 | 0.7189 | |
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| 0.3453 | 49.01 | 2775 | 0.8822 | 0.7189 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 1.13.1 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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