---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: VideoMAE-URFall_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-URFall_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: 0.1097
- Accuracy: 0.9743

## 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: 11820

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.1366        | 0.1   | 1183  | 1.9949          | 0.5648   |
| 0.8345        | 1.1   | 2366  | 0.8534          | 0.7909   |
| 0.4507        | 2.1   | 3549  | 0.5013          | 0.8644   |
| 0.2105        | 3.1   | 4732  | 0.3949          | 0.8949   |
| 0.1062        | 4.1   | 5915  | 0.2903          | 0.9258   |
| 0.0427        | 5.1   | 7098  | 0.2665          | 0.9298   |
| 0.0028        | 6.1   | 8281  | 0.2535          | 0.9379   |
| 0.0018        | 7.1   | 9464  | 0.1895          | 0.9558   |
| 0.0133        | 8.1   | 10647 | 0.1128          | 0.9736   |
| 0.1176        | 9.1   | 11820 | 0.1097          | 0.9743   |


### Framework versions

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