Model save
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README.md
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---
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license: cc-by-nc-4.0
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base_model: MCG-NJU/videomae-base-finetuned-kinetics
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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-dcsass-shoplifting-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-kinetics-finetuned-dcsass-shoplifting-subset
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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: 0.3803
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- Accuracy: 0.8874
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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: 780
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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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| 0.3314 | 0.2013 | 157 | 0.6146 | 0.8219 |
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| 0.3263 | 1.2013 | 314 | 0.6184 | 0.8288 |
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| 0.6332 | 2.2013 | 471 | 0.4275 | 0.8425 |
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| 0.0405 | 3.2013 | 628 | 0.7687 | 0.8425 |
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| 0.1579 | 4.1949 | 780 | 0.5852 | 0.8562 |
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### Framework versions
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- Transformers 4.40.1
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- Pytorch 2.2.1+cu121
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- Datasets 2.19.0
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- Tokenizers 0.19.1
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runs/May01_17-58-26_f9a9d4427412/events.out.tfevents.1714588618.f9a9d4427412.2055.1
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version https://git-lfs.github.com/spec/v1
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oid sha256:8c5ef647bcffe516005b3b1334b3b565a327e0afbcd91c9e4b2bb1df1523194d
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size 411
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