---
library_name: transformers
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-ucf-crimev3
  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. -->

# videomae-base-finetuned-ucf-crimev3

This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2215
- Accuracy: 0.3545

## 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: 3e-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_steps: 500
- training_steps: 1230

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2429        | 1.0   | 42   | 1.8114          | 0.3091   |
| 1.2691        | 2.0   | 84   | 1.8293          | 0.3273   |
| 0.9197        | 3.0   | 126  | 1.8547          | 0.3364   |
| 0.9611        | 4.0   | 168  | 1.8772          | 0.3455   |
| 0.848         | 5.0   | 210  | 1.8690          | 0.3636   |
| 1.0474        | 6.0   | 252  | 1.8581          | 0.3636   |
| 0.7281        | 7.0   | 294  | 1.9003          | 0.3909   |
| 0.6033        | 8.0   | 336  | 2.0023          | 0.3364   |
| 0.3703        | 9.0   | 378  | 2.1459          | 0.3364   |
| 0.4539        | 10.0  | 420  | 2.2215          | 0.3545   |


### Framework versions

- Transformers 4.47.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3