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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-kinetics-finetuned-rwf2000-epochs8-batch8-kb |
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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-kinetics-finetuned-rwf2000-epochs8-batch8-kb |
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This model is a fine-tuned version of [MCG-NJU/videomae-base-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-base-finetuned-kinetics) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5482 |
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- Accuracy: 0.7298 |
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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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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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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: 3200 |
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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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| 0.4492 | 0.06 | 200 | 0.2361 | 0.905 | |
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| 0.3517 | 1.06 | 400 | 0.5648 | 0.8137 | |
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| 0.2255 | 2.06 | 600 | 0.7592 | 0.7575 | |
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| 0.1983 | 3.06 | 800 | 0.4803 | 0.835 | |
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| 0.2305 | 4.06 | 1000 | 0.4290 | 0.8738 | |
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| 0.1276 | 5.06 | 1200 | 0.4317 | 0.8762 | |
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| 0.1597 | 6.06 | 1400 | 1.3708 | 0.6937 | |
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| 0.3088 | 7.06 | 1600 | 0.3974 | 0.8862 | |
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| 0.2687 | 8.06 | 1800 | 0.5986 | 0.85 | |
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| 0.2085 | 9.06 | 2000 | 0.4264 | 0.8862 | |
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| 0.1338 | 10.06 | 2200 | 0.5015 | 0.8675 | |
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| 0.2191 | 11.06 | 2400 | 0.7103 | 0.845 | |
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| 0.2255 | 12.06 | 2600 | 0.4939 | 0.8762 | |
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| 0.0298 | 13.06 | 2800 | 0.6338 | 0.8612 | |
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| 0.0687 | 14.06 | 3000 | 0.5350 | 0.8738 | |
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| 0.0146 | 15.06 | 3200 | 0.4770 | 0.8838 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.2 |
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