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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-groub13-14-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-groub13-14-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: 0.9463 |
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- Accuracy: 1.0 |
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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: 4 |
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- eval_batch_size: 4 |
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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: 224 |
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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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| 3.0689 | 0.07 | 15 | 2.9460 | 0.1 | |
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| 3.1203 | 1.07 | 30 | 2.7839 | 0.15 | |
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| 2.8375 | 2.07 | 45 | 2.6131 | 0.2 | |
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| 2.619 | 3.07 | 60 | 2.5076 | 0.2 | |
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| 2.455 | 4.07 | 75 | 2.4382 | 0.15 | |
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| 2.4831 | 5.07 | 90 | 2.3911 | 0.25 | |
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| 2.5183 | 6.07 | 105 | 2.3353 | 0.3 | |
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| 2.4267 | 7.07 | 120 | 2.2589 | 0.35 | |
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| 2.257 | 8.07 | 135 | 2.1845 | 0.4 | |
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| 2.1795 | 9.07 | 150 | 2.0329 | 0.6 | |
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| 1.9706 | 10.07 | 165 | 1.7614 | 0.9 | |
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| 1.7866 | 11.07 | 180 | 1.4249 | 0.95 | |
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| 1.4293 | 12.07 | 195 | 1.1991 | 0.9 | |
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| 0.9984 | 13.07 | 210 | 1.0114 | 0.95 | |
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| 0.9409 | 14.06 | 224 | 0.9463 | 1.0 | |
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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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