---
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-base-cart-activity-v2-imagefolder
  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-cart-activity-v2-imagefolder

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: 0.1807
- Accuracy: 0.9533

## 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: 2
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 17145

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Accuracy |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|
| 0.3978        | 0.0334  | 572   | 0.9201          | 0.5969   |
| 0.294         | 1.0334  | 1144  | 0.3255          | 0.9027   |
| 0.5046        | 2.0334  | 1716  | 0.6951          | 0.7712   |
| 0.3563        | 3.0334  | 2288  | 0.2648          | 0.9284   |
| 0.4592        | 4.0334  | 2860  | 0.2469          | 0.9167   |
| 0.1586        | 5.0334  | 3432  | 0.2294          | 0.9354   |
| 0.1798        | 6.0334  | 4004  | 0.2167          | 0.9346   |
| 0.3834        | 7.0334  | 4576  | 0.2334          | 0.9292   |
| 0.1425        | 8.0334  | 5148  | 0.2864          | 0.9253   |
| 0.1253        | 9.0334  | 5720  | 0.2605          | 0.9183   |
| 0.2152        | 10.0334 | 6292  | 0.2687          | 0.9276   |
| 0.1605        | 11.0334 | 6864  | 0.2657          | 0.9237   |
| 0.1927        | 12.0334 | 7436  | 0.2134          | 0.9424   |
| 0.1003        | 13.0334 | 8008  | 0.2687          | 0.9300   |
| 0.2421        | 14.0334 | 8580  | 0.2345          | 0.9307   |
| 0.1248        | 15.0334 | 9152  | 0.3142          | 0.9136   |
| 0.2701        | 16.0334 | 9724  | 0.2174          | 0.9409   |
| 0.1817        | 17.0334 | 10296 | 0.2328          | 0.9416   |
| 0.1447        | 18.0334 | 10868 | 0.2165          | 0.9393   |
| 0.1101        | 19.0334 | 11440 | 0.2811          | 0.9300   |
| 0.1832        | 20.0334 | 12012 | 0.2230          | 0.9424   |
| 0.1064        | 21.0334 | 12584 | 0.1843          | 0.9479   |
| 0.2109        | 22.0334 | 13156 | 0.2523          | 0.9323   |
| 0.0486        | 23.0334 | 13728 | 0.2485          | 0.9377   |
| 0.1455        | 24.0334 | 14300 | 0.1807          | 0.9533   |
| 0.0695        | 25.0334 | 14872 | 0.2349          | 0.9393   |
| 0.2897        | 26.0334 | 15444 | 0.2229          | 0.9393   |
| 0.0949        | 27.0334 | 16016 | 0.2156          | 0.9486   |
| 0.0849        | 28.0334 | 16588 | 0.2122          | 0.9479   |
| 0.0957        | 29.0325 | 17145 | 0.2072          | 0.9502   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0