---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/timesformer-hr-finetuned-k600
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: timesformer-crime-detection
  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. -->

# timesformer-crime-detection

This model is a fine-tuned version of [facebook/timesformer-hr-finetuned-k600](https://huggingface.co/facebook/timesformer-hr-finetuned-k600) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0006
- Accuracy: 1.0

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.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_steps: 500
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 41   | 0.0006          | 1.0      |
| No log        | 2.0   | 82   | 0.0001          | 1.0      |
| 0.2323        | 3.0   | 123  | 0.0001          | 1.0      |
| 0.2323        | 4.0   | 164  | 0.0000          | 1.0      |
| 0.0           | 5.0   | 205  | 0.0000          | 1.0      |


### Framework versions

- Transformers 4.52.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1