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README.md
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---
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license: mit
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base_model: google/vivit-b-16x2-kinetics400
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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: vivit-b-16x2-kinetics400-finetuned-vivit-severity
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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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# vivit-b-16x2-kinetics400-finetuned-vivit-severity
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This model is a fine-tuned version of [google/vivit-b-16x2-kinetics400](https://huggingface.co/google/vivit-b-16x2-kinetics400) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0088
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- Accuracy: 0.8530
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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: 1
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- eval_batch_size: 1
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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: 5210
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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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| 2.0504 | 0.1 | 521 | 0.9279 | 0.8280 |
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| 1.1617 | 1.1 | 1042 | 0.9890 | 0.8280 |
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| 0.5088 | 2.1 | 1563 | 0.8413 | 0.8172 |
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| 0.7947 | 3.1 | 2084 | 0.7631 | 0.8423 |
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| 0.0028 | 4.1 | 2605 | 0.8718 | 0.8459 |
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| 0.7502 | 5.1 | 3126 | 0.9022 | 0.8495 |
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| 0.814 | 6.1 | 3647 | 0.8467 | 0.8423 |
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| 0.5251 | 7.1 | 4168 | 0.8914 | 0.8602 |
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| 0.9977 | 8.1 | 4689 | 0.9599 | 0.8530 |
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| 0.0007 | 9.1 | 5210 | 1.0088 | 0.8530 |
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### Framework versions
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- Transformers 4.42.4
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- Pytorch 2.0.1+cu117
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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