transformers pytorch tensorboard safetensors videomae video-classification generated_from_trainer base_model:MCG-NJU/videomae-base license:cc-by-nc-4.0 endpoints_compatible region:us
---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned
  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

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: 0.2738
- Accuracy: 0.9360

## 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: 184

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2081        | 0.13  | 24   | 0.8609          | 0.8488   |
| 0.9402        | 1.13  | 48   | 1.6943          | 0.3314   |
| 0.7736        | 2.13  | 72   | 0.2337          | 0.9535   |
| 0.9935        | 3.13  | 96   | 0.2556          | 0.9535   |
| 0.4901        | 4.13  | 120  | 0.3547          | 0.8837   |
| 0.43          | 5.13  | 144  | 0.7274          | 0.6919   |
| 0.4121        | 6.13  | 168  | 0.2916          | 0.9244   |
| 0.3765        | 7.09  | 184  | 0.2738          | 0.9360   |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.13.3
