---
library_name: transformers
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: VideoMAE_BdSLW60_FrameRateCorrected_withAug_100
  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_BdSLW60_FrameRateCorrected_withAug_100

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: 0.5588
- Accuracy: 0.8973

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 22400

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Accuracy |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|
| 3.0699        | 0.0400  | 897   | 2.4541          | 0.4753   |
| 0.6366        | 1.0401  | 1795  | 0.6832          | 0.84     |
| 0.2253        | 2.0401  | 2693  | 0.3464          | 0.9024   |
| 0.1229        | 3.0401  | 3591  | 0.1467          | 0.9647   |
| 0.1045        | 4.0400  | 4488  | 0.1459          | 0.9635   |
| 0.0631        | 5.0401  | 5386  | 0.1313          | 0.9718   |
| 0.0736        | 6.0401  | 6284  | 0.1807          | 0.9635   |
| 0.0673        | 7.0401  | 7182  | 0.1464          | 0.9694   |
| 0.0239        | 8.0400  | 8079  | 0.1932          | 0.9576   |
| 0.0868        | 9.0401  | 8977  | 0.0563          | 0.9882   |
| 0.0016        | 10.0401 | 9875  | 0.0844          | 0.9776   |
| 0.0318        | 11.0401 | 10773 | 0.1123          | 0.9753   |
| 0.0144        | 12.0400 | 11670 | 0.0499          | 0.9894   |
| 0.0028        | 13.0401 | 12568 | 0.0809          | 0.9871   |
| 0.0074        | 14.0401 | 13466 | 0.0455          | 0.9929   |
| 0.0002        | 15.0401 | 14364 | 0.0581          | 0.9906   |
| 0.0077        | 16.0400 | 15261 | 0.0502          | 0.9894   |
| 0.0005        | 17.0401 | 16159 | 0.0407          | 0.9929   |
| 0.0004        | 18.0401 | 17057 | 0.0550          | 0.9906   |
| 0.0001        | 19.0401 | 17955 | 0.0583          | 0.9929   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1