---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-Cheh2_ucf_light_demo-10epochs
  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-Cheh2_ucf_light_demo-10epochs

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: 1.6448
- Accuracy: 0.5270

## 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: 15010

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 2.3441        | 0.1001 | 1502  | 2.3923          | 0.2469   |
| 1.6506        | 1.1001 | 3004  | 2.0596          | 0.3513   |
| 1.1963        | 2.1001 | 4506  | 2.0148          | 0.4035   |
| 1.5381        | 3.1001 | 6008  | 1.8796          | 0.4262   |
| 1.5438        | 4.1001 | 7510  | 1.8851          | 0.4398   |
| 1.225         | 5.1001 | 9012  | 1.7874          | 0.4649   |
| 1.038         | 6.1001 | 10514 | 1.7263          | 0.4852   |
| 1.0129        | 7.1001 | 12016 | 1.7192          | 0.5046   |
| 1.0309        | 8.1001 | 13518 | 1.6448          | 0.5270   |
| 0.91          | 9.0994 | 15010 | 1.6655          | 0.5144   |


### Framework versions

- Transformers 4.43.4
- Pytorch 2.4.1
- Datasets 2.20.0
- Tokenizers 0.19.1