---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-finetuned-v2
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/siccimo/huggingface/runs/n6qav2ji)
# videomae-finetuned-v2

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: 0.4511
- Accuracy: 0.825

## 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: 16
- eval_batch_size: 16
- 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: 90

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 0.0556  | 5    | 0.6644          | 0.52     |
| 0.649         | 1.0556  | 10   | 0.5890          | 0.68     |
| 0.649         | 2.0556  | 15   | 0.6915          | 0.48     |
| 0.5368        | 3.0556  | 20   | 0.5428          | 0.48     |
| 0.5368        | 4.0556  | 25   | 0.2507          | 0.92     |
| 0.3519        | 5.0556  | 30   | 0.6503          | 0.68     |
| 0.3519        | 6.0556  | 35   | 0.6544          | 0.68     |
| 0.4579        | 7.0556  | 40   | 0.2332          | 0.92     |
| 0.4579        | 8.0556  | 45   | 0.4506          | 0.88     |
| 0.3166        | 9.0556  | 50   | 0.2587          | 0.88     |
| 0.3166        | 10.0556 | 55   | 0.1353          | 0.92     |
| 0.2761        | 11.0556 | 60   | 0.3067          | 0.92     |
| 0.2761        | 12.0556 | 65   | 0.4782          | 0.84     |
| 0.2316        | 13.0556 | 70   | 0.3868          | 0.84     |
| 0.2316        | 14.0556 | 75   | 0.3565          | 0.88     |
| 0.173         | 15.0556 | 80   | 0.3623          | 0.92     |
| 0.173         | 16.0556 | 85   | 0.2870          | 0.92     |
| 0.1488        | 17.0556 | 90   | 0.2836          | 0.92     |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1