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

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: 1.8802
- Accuracy: 0.6944

## 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: 5
- eval_batch_size: 5
- 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: 1200

### Training results

| Training Loss | Epoch    | Step | Validation Loss | Accuracy |
|:-------------:|:--------:|:----:|:---------------:|:--------:|
| 1.6771        | 16.0033  | 100  | 1.5844          | 0.2222   |
| 0.2052        | 33.0017  | 200  | 1.8833          | 0.4722   |
| 0.6001        | 49.005   | 300  | 1.4486          | 0.6944   |
| 0.3118        | 66.0033  | 400  | 0.1618          | 0.9722   |
| 0.0046        | 83.0017  | 500  | 2.1274          | 0.6944   |
| 0.0528        | 99.005   | 600  | 1.8246          | 0.7222   |
| 0.0174        | 116.0033 | 700  | 1.9694          | 0.7222   |
| 0.2597        | 133.0017 | 800  | 2.0549          | 0.6944   |
| 0.0505        | 149.005  | 900  | 1.9087          | 0.7222   |
| 0.0014        | 166.0033 | 1000 | 2.0244          | 0.6944   |
| 0.0324        | 183.0017 | 1100 | 1.5456          | 0.75     |
| 0.0011        | 199.005  | 1200 | 1.8802          | 0.6944   |


### Framework versions

- Transformers 4.45.0
- Pytorch 2.4.1+cu118
- Datasets 3.0.0
- Tokenizers 0.20.0