---
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-finetuned-ucf101-subset-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-finetuned-ucf101-subset-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: 2.5315
- Accuracy: 0.6389

## 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: 3
- eval_batch_size: 3
- 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: 2000

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.8253        | 9.005   | 100  | 1.7977          | 0.1667   |
| 1.6427        | 19.005  | 200  | 2.1211          | 0.1667   |
| 1.0603        | 29.005  | 300  | 2.5370          | 0.1944   |
| 0.6361        | 39.005  | 400  | 1.9683          | 0.4444   |
| 0.7149        | 49.005  | 500  | 2.8125          | 0.3889   |
| 0.3396        | 59.005  | 600  | 2.2497          | 0.5556   |
| 0.3026        | 69.005  | 700  | 1.7178          | 0.6389   |
| 0.3043        | 79.005  | 800  | 2.5029          | 0.6111   |
| 0.1636        | 89.005  | 900  | 2.7748          | 0.6111   |
| 0.1292        | 99.005  | 1000 | 2.1868          | 0.6389   |
| 0.5229        | 109.005 | 1100 | 2.4543          | 0.6111   |
| 0.0016        | 119.005 | 1200 | 1.7452          | 0.75     |
| 0.0013        | 129.005 | 1300 | 2.5026          | 0.6111   |
| 0.0011        | 139.005 | 1400 | 2.3153          | 0.6389   |
| 0.0011        | 149.005 | 1500 | 1.7536          | 0.75     |
| 0.0028        | 159.005 | 1600 | 2.5384          | 0.6389   |
| 0.0605        | 169.005 | 1700 | 2.6368          | 0.6111   |
| 0.2064        | 179.005 | 1800 | 2.3678          | 0.6667   |
| 0.0013        | 189.005 | 1900 | 2.4561          | 0.6389   |
| 0.0009        | 199.005 | 2000 | 2.5315          | 0.6389   |


### Framework versions

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