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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-CAER-SAMPLE
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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-CAER-SAMPLE
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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: 1.9485
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- Accuracy: 0.2427
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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: 2100
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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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| 2.4781 | 0.09 | 196 | 1.8166 | 0.2439 |
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| 2.0142 | 1.09 | 392 | 2.2946 | 0.1951 |
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| 1.2947 | 2.09 | 588 | 1.6998 | 0.3659 |
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| 0.8486 | 3.09 | 784 | 2.0369 | 0.2195 |
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| 0.2636 | 4.09 | 980 | 1.9748 | 0.3171 |
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| 0.2805 | 5.09 | 1176 | 2.3563 | 0.3659 |
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| 0.0923 | 6.09 | 1372 | 2.3754 | 0.3659 |
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| 0.1543 | 7.09 | 1568 | 2.7737 | 0.3171 |
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| 0.0387 | 8.09 | 1764 | 2.6676 | 0.3659 |
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| 0.0101 | 9.09 | 1960 | 2.7895 | 0.3415 |
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| 0.0662 | 10.07 | 2100 | 2.7728 | 0.3415 |
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### Framework versions
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- Transformers 4.38.2
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- Pytorch 2.1.0
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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