---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-large-cctv-brawl_extended_v2
  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-large-cctv-brawl_extended_v2

This model is a fine-tuned version of [MCG-NJU/videomae-large](https://huggingface.co./MCG-NJU/videomae-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7025
- Accuracy: 0.8993

## 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-07
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 37695

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.4212        | 0.07  | 2514  | 0.4737          | 0.7236   |
| 0.2813        | 1.07  | 5028  | 0.3922          | 0.8350   |
| 0.1918        | 2.07  | 7542  | 0.5665          | 0.8734   |
| 0.2002        | 3.07  | 10056 | 0.6058          | 0.8808   |
| 0.1921        | 4.07  | 12570 | 0.6136          | 0.8867   |
| 0.1713        | 5.07  | 15084 | 0.6446          | 0.8914   |
| 0.006         | 6.07  | 17598 | 0.6783          | 0.8918   |
| 0.004         | 7.07  | 20112 | 0.7586          | 0.8863   |
| 0.201         | 8.07  | 22626 | 0.7732          | 0.8906   |
| 0.0237        | 9.07  | 25140 | 0.7025          | 0.8993   |
| 0.0003        | 10.07 | 27654 | 0.7510          | 0.8957   |
| 0.1943        | 11.07 | 30168 | 0.7849          | 0.8989   |
| 0.0001        | 12.07 | 32682 | 0.8075          | 0.8981   |
| 0.0           | 13.07 | 35196 | 0.8347          | 0.8961   |
| 0.0001        | 14.07 | 37695 | 0.8329          | 0.8985   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1