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

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: 0.1136
- Accuracy: 0.9736

## 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: 11950

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.9014        | 0.1   | 1196  | 2.1529          | 0.5014   |
| 0.8259        | 1.1   | 2392  | 1.0095          | 0.7478   |
| 0.4316        | 2.1   | 3588  | 0.6168          | 0.8361   |
| 0.0665        | 3.1   | 4784  | 0.3693          | 0.8952   |
| 0.3185        | 4.1   | 5980  | 0.2011          | 0.9456   |
| 0.2362        | 5.1   | 7176  | 0.2938          | 0.9211   |
| 0.0728        | 6.1   | 8372  | 0.1560          | 0.9563   |
| 0.0332        | 7.1   | 9568  | 0.1403          | 0.9620   |
| 0.0036        | 8.1   | 10764 | 0.1207          | 0.9705   |
| 0.0026        | 9.1   | 11950 | 0.1136          | 0.9736   |


### Framework versions

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