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---
library_name: transformers
license: mit
base_model: prathameshdalal/vivit-b-16x2-kinetics400-UCF-Crime
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vivit-b-16x2-kinetics400-UCF-Crime-finetuned-AbnormalVideosOnly
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# vivit-b-16x2-kinetics400-UCF-Crime-finetuned-AbnormalVideosOnly
This model is a fine-tuned version of [prathameshdalal/vivit-b-16x2-kinetics400-UCF-Crime](https://huggingface.co/prathameshdalal/vivit-b-16x2-kinetics400-UCF-Crime) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6304
- Accuracy: 0.0962
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 202
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 2.5324 | 0.5050 | 102 | 2.6516 | 0.0739 |
| 2.4308 | 1.4950 | 202 | 2.6304 | 0.0962 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.1.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
|