---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: VideoMAE-MultipleCameraFall
  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-MultipleCameraFall

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: 0.0944
- Accuracy: 0.9752

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 11770

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.801         | 0.1   | 1178  | 2.0143          | 0.5181   |
| 0.7407        | 1.1   | 2356  | 0.7707          | 0.8052   |
| 0.4488        | 2.1   | 3534  | 0.4310          | 0.8839   |
| 0.1402        | 3.1   | 4712  | 0.3790          | 0.8934   |
| 0.1608        | 4.1   | 5890  | 0.2916          | 0.9194   |
| 0.0133        | 5.1   | 7068  | 0.1776          | 0.9542   |
| 0.0806        | 6.1   | 8246  | 0.1715          | 0.9582   |
| 0.0132        | 7.1   | 9424  | 0.1474          | 0.9656   |
| 0.0017        | 8.1   | 10602 | 0.1038          | 0.9722   |
| 0.002         | 9.1   | 11770 | 0.0944          | 0.9752   |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1