Steve Chiou
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update model card README.md
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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-engine-subset-20230313
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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-engine-subset-20230313
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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: 0.8913
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- Accuracy: 0.6745
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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: 6
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- eval_batch_size: 6
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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: 1110
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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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| 2.6212 | 0.03 | 38 | 2.3629 | 0.3774 |
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| 2.455 | 1.03 | 76 | 2.3674 | 0.2170 |
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| 2.4311 | 2.03 | 114 | 2.2191 | 0.3231 |
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| 2.2768 | 3.03 | 152 | 2.1227 | 0.3608 |
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| 1.7528 | 4.03 | 190 | 1.7296 | 0.4363 |
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| 1.5381 | 5.03 | 228 | 1.5016 | 0.4340 |
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| 1.407 | 6.03 | 266 | 1.2878 | 0.5448 |
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| 1.1053 | 7.03 | 304 | 1.5210 | 0.4009 |
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| 1.0893 | 8.03 | 342 | 1.3902 | 0.4623 |
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| 0.8136 | 9.03 | 380 | 1.6456 | 0.4033 |
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| 0.9565 | 10.03 | 418 | 1.1826 | 0.5613 |
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| 1.0147 | 11.03 | 456 | 1.2099 | 0.5118 |
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| 0.9125 | 12.03 | 494 | 1.1850 | 0.5495 |
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| 0.7091 | 13.03 | 532 | 1.2324 | 0.5354 |
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| 0.7361 | 14.03 | 570 | 1.0225 | 0.6226 |
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| 0.6979 | 15.03 | 608 | 1.0738 | 0.5590 |
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| 0.5265 | 16.03 | 646 | 1.1062 | 0.5873 |
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| 0.5651 | 17.03 | 684 | 1.1402 | 0.5802 |
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| 0.7182 | 18.03 | 722 | 1.0974 | 0.5802 |
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| 0.6582 | 19.03 | 760 | 1.0529 | 0.6179 |
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| 0.5709 | 20.03 | 798 | 0.9655 | 0.6344 |
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| 0.4808 | 21.03 | 836 | 1.0441 | 0.6226 |
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| 0.5816 | 22.03 | 874 | 0.9445 | 0.6439 |
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| 0.5057 | 23.03 | 912 | 1.0248 | 0.6321 |
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| 0.6253 | 24.03 | 950 | 0.9518 | 0.6604 |
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| 0.6841 | 25.03 | 988 | 0.8913 | 0.6745 |
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| 0.5933 | 26.03 | 1026 | 0.9013 | 0.6439 |
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| 0.389 | 27.03 | 1064 | 0.9090 | 0.6627 |
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| 0.3705 | 28.03 | 1102 | 0.8936 | 0.6722 |
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| 0.6043 | 29.01 | 1110 | 0.8942 | 0.6722 |
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### Framework versions
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- Transformers 4.26.1
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- Pytorch 1.12.1+cu113
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- Datasets 2.10.1
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- Tokenizers 0.13.2
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