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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-groub1-finetuned-SLT-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-groub1-finetuned-SLT-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: 0.3056 |
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- Accuracy: 0.9767 |
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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: 1008 |
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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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| 3.8889 | 0.06 | 64 | 3.6733 | 0.0465 | |
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| 3.8474 | 1.06 | 128 | 3.7358 | 0.0698 | |
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| 3.7886 | 2.06 | 192 | 3.6336 | 0.0465 | |
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| 3.7398 | 3.06 | 256 | 3.5894 | 0.0698 | |
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| 3.7363 | 4.06 | 320 | 3.4637 | 0.0698 | |
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| 3.6345 | 5.06 | 384 | 3.3875 | 0.0698 | |
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| 3.2723 | 6.06 | 448 | 3.2156 | 0.1163 | |
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| 3.2814 | 7.06 | 512 | 2.7291 | 0.7209 | |
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| 2.7245 | 8.06 | 576 | 1.9657 | 0.8140 | |
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| 1.8616 | 9.06 | 640 | 1.2883 | 0.8837 | |
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| 1.3802 | 10.06 | 704 | 0.8116 | 0.9302 | |
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| 1.0416 | 11.06 | 768 | 0.5877 | 0.9535 | |
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| 0.6415 | 12.06 | 832 | 0.4426 | 0.9767 | |
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| 0.5546 | 13.06 | 896 | 0.3599 | 0.9767 | |
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| 0.4495 | 14.06 | 960 | 0.3212 | 0.9767 | |
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| 0.2214 | 15.05 | 1008 | 0.3056 | 0.9767 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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