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

This model is a fine-tuned version of [MCG-NJU/videomae-base-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-base-finetuned-kinetics) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7131
- Accuracy: 0.5080

## 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: 4
- eval_batch_size: 4
- 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: 2457.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0402        | 0.08  | 200  | 1.2844          | 0.4647   |
| 0.0003        | 0.16  | 400  | 1.6560          | 0.4692   |
| 0.0001        | 0.24  | 600  | 2.0519          | 0.4510   |
| 0.0001        | 0.33  | 800  | 1.6676          | 0.4396   |
| 0.0001        | 1.07  | 1000 | 2.1058          | 0.4305   |
| 0.0001        | 1.15  | 1200 | 2.1659          | 0.4419   |
| 0.0           | 1.24  | 1400 | 2.2195          | 0.4374   |
| 0.0           | 1.32  | 1600 | 2.3093          | 0.4351   |
| 0.0013        | 2.07  | 1800 | 2.1501          | 0.5604   |
| 0.0           | 2.15  | 2000 | 2.2250          | 0.5148   |
| 0.0           | 2.23  | 2200 | 2.6678          | 0.5330   |
| 0.0           | 2.31  | 2400 | 2.7131          | 0.5080   |


### Framework versions

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