---
library_name: transformers
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: videomae-base-videoMAE
  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-videoMAE

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: 1.6956
- Accuracy: 0.8571
- Precision: 0.8929
- Recall: 0.8571
- F1: 0.8571

## 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: 12825

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4984        | 1.0     | 514   | 1.3741          | 0.4286   | 0.1837    | 0.4286 | 0.2571 |
| 0.3492        | 2.0     | 1028  | 0.9819          | 0.4286   | 0.1837    | 0.4286 | 0.2571 |
| 0.4071        | 3.0     | 1542  | 2.8074          | 0.4286   | 0.1837    | 0.4286 | 0.2571 |
| 0.3151        | 4.0     | 2056  | 0.2223          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.0053        | 5.0     | 2570  | 4.9944          | 0.4286   | 0.1837    | 0.4286 | 0.2571 |
| 0.0017        | 6.0     | 3084  | 0.3940          | 0.8571   | 0.8857    | 0.8571 | 0.8508 |
| 0.0092        | 7.0     | 3598  | 3.8118          | 0.4286   | 0.1837    | 0.4286 | 0.2571 |
| 0.0003        | 8.0     | 4112  | 4.5879          | 0.4286   | 0.1837    | 0.4286 | 0.2571 |
| 0.0973        | 9.0     | 4626  | 2.7723          | 0.4286   | 0.1837    | 0.4286 | 0.2571 |
| 0.0011        | 10.0    | 5140  | 4.0052          | 0.4286   | 0.1837    | 0.4286 | 0.2571 |
| 0.0           | 11.0    | 5654  | 1.5523          | 0.5714   | 0.7857    | 0.5714 | 0.5143 |
| 0.0           | 12.0    | 6168  | 1.4310          | 0.7143   | 0.8286    | 0.7143 | 0.7024 |
| 0.0           | 13.0    | 6682  | 1.4236          | 0.8571   | 0.8929    | 0.8571 | 0.8571 |
| 0.0           | 14.0    | 7196  | 1.4245          | 0.8571   | 0.8929    | 0.8571 | 0.8571 |
| 0.0           | 15.0    | 7710  | 1.4416          | 0.8571   | 0.8929    | 0.8571 | 0.8571 |
| 0.0           | 16.0    | 8224  | 1.4639          | 0.8571   | 0.8929    | 0.8571 | 0.8571 |
| 0.0           | 17.0    | 8738  | 1.4884          | 0.8571   | 0.8929    | 0.8571 | 0.8571 |
| 0.0           | 18.0    | 9252  | 1.5161          | 0.8571   | 0.8929    | 0.8571 | 0.8571 |
| 0.0           | 19.0    | 9766  | 1.5452          | 0.8571   | 0.8929    | 0.8571 | 0.8571 |
| 0.0           | 20.0    | 10280 | 1.5755          | 0.8571   | 0.8929    | 0.8571 | 0.8571 |
| 0.0           | 21.0    | 10794 | 1.6078          | 0.8571   | 0.8929    | 0.8571 | 0.8571 |
| 0.0           | 22.0    | 11308 | 1.6386          | 0.8571   | 0.8929    | 0.8571 | 0.8571 |
| 0.0           | 23.0    | 11822 | 1.6669          | 0.8571   | 0.8929    | 0.8571 | 0.8571 |
| 0.0           | 24.0    | 12336 | 1.6868          | 0.8571   | 0.8929    | 0.8571 | 0.8571 |
| 0.0           | 24.9514 | 12825 | 1.6956          | 0.8571   | 0.8929    | 0.8571 | 0.8571 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1