---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-slrbd002
  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-slrbd002

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: 0.4824
- Accuracy: 0.875

## 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: 1800

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.6684        | 0.05  | 90   | 3.6696          | 0.025    |
| 3.4781        | 1.05  | 180  | 3.3494          | 0.1313   |
| 3.2885        | 2.05  | 270  | 3.1702          | 0.125    |
| 2.7847        | 3.05  | 360  | 2.7654          | 0.2562   |
| 2.4107        | 4.05  | 450  | 2.6756          | 0.2437   |
| 1.7783        | 5.05  | 540  | 1.9950          | 0.4813   |
| 1.3054        | 6.05  | 630  | 1.4908          | 0.6188   |
| 0.5868        | 7.05  | 720  | 1.4568          | 0.6188   |
| 0.4388        | 8.05  | 810  | 0.9511          | 0.7312   |
| 0.2187        | 9.05  | 900  | 1.1580          | 0.65     |
| 0.1665        | 10.05 | 990  | 0.6565          | 0.8313   |
| 0.0959        | 11.05 | 1080 | 0.5731          | 0.8562   |
| 0.0273        | 12.05 | 1170 | 0.6637          | 0.8063   |
| 0.02          | 13.05 | 1260 | 0.5048          | 0.875    |
| 0.0137        | 14.05 | 1350 | 0.4815          | 0.8688   |
| 0.0261        | 15.05 | 1440 | 0.5649          | 0.8438   |
| 0.013         | 16.05 | 1530 | 0.5419          | 0.8375   |
| 0.0123        | 17.05 | 1620 | 0.4864          | 0.8812   |
| 0.0527        | 18.05 | 1710 | 0.4725          | 0.8875   |
| 0.011         | 19.05 | 1800 | 0.4824          | 0.875    |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0