---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: VideoMAE-URFall_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-URFall_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: 0.1220
- Accuracy: 0.9691

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.2186        | 0.1   | 1183  | 2.0737          | 0.5172   |
| 0.8664        | 1.1   | 2366  | 0.6972          | 0.8211   |
| 0.3324        | 2.1   | 3549  | 0.6007          | 0.8372   |
| 0.1919        | 3.1   | 4732  | 0.5145          | 0.8651   |
| 0.1457        | 4.1   | 5915  | 0.2822          | 0.9221   |
| 0.0996        | 5.1   | 7098  | 0.2434          | 0.9359   |
| 0.0159        | 6.1   | 8281  | 0.1729          | 0.9547   |
| 0.0018        | 7.1   | 9464  | 0.1307          | 0.9649   |
| 0.001         | 8.1   | 10647 | 0.1524          | 0.9640   |
| 0.0013        | 9.1   | 11820 | 0.1220          | 0.9691   |


### Framework versions

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