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--- |
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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 was trained from scratch on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1801 |
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- Accuracy: 0.5412 |
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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: 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: 4920 |
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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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| 0.3212 | 0.0502 | 247 | 0.5765 | 0.7898 | |
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| 0.3799 | 1.0502 | 494 | 0.4347 | 0.8042 | |
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| 0.1638 | 2.0502 | 741 | 0.6744 | 0.6560 | |
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| 0.1194 | 3.0502 | 988 | 0.3914 | 0.8500 | |
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| 0.2124 | 4.0502 | 1235 | 0.8541 | 0.7002 | |
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| 0.0289 | 5.0502 | 1482 | 2.8893 | 0.5087 | |
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| 0.0909 | 6.0502 | 1729 | 1.3700 | 0.6822 | |
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| 0.0729 | 7.0502 | 1976 | 1.4459 | 0.6671 | |
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| 0.0122 | 8.0502 | 2223 | 1.9108 | 0.6382 | |
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| 0.0269 | 9.0502 | 2470 | 2.4835 | 0.5734 | |
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| 0.0659 | 10.0502 | 2717 | 2.8008 | 0.6112 | |
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| 0.0371 | 11.0502 | 2964 | 2.7996 | 0.5996 | |
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| 0.1188 | 12.0502 | 3211 | 2.8353 | 0.6063 | |
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| 0.0203 | 13.0502 | 3458 | 2.1282 | 0.6544 | |
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| 0.053 | 14.0502 | 3705 | 2.5461 | 0.6431 | |
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| 0.0006 | 15.0502 | 3952 | 2.9020 | 0.6257 | |
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| 0.0365 | 16.0502 | 4199 | 3.0216 | 0.5914 | |
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| 0.0005 | 17.0502 | 4446 | 2.8913 | 0.6036 | |
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| 0.0003 | 18.0502 | 4693 | 2.9041 | 0.6098 | |
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| 0.0003 | 19.0461 | 4920 | 2.9829 | 0.6028 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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