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

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: 0.1003
- Accuracy: 0.9722

## 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: 11650

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.1435        | 0.1   | 1165  | 2.2165          | 0.4536   |
| 0.8432        | 1.1   | 2330  | 0.7595          | 0.8010   |
| 0.4293        | 2.1   | 3495  | 0.5219          | 0.8578   |
| 0.2377        | 3.1   | 4660  | 0.3852          | 0.8972   |
| 0.1604        | 4.1   | 5825  | 0.2505          | 0.9349   |
| 0.0418        | 5.1   | 6990  | 0.2070          | 0.9431   |
| 0.0048        | 6.1   | 8155  | 0.1811          | 0.9520   |
| 0.0051        | 7.1   | 9320  | 0.1311          | 0.9634   |
| 0.0012        | 8.1   | 10485 | 0.1096          | 0.9698   |
| 0.0857        | 9.1   | 11650 | 0.1003          | 0.9722   |


### Framework versions

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