---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: videomae-base-finetuned-numbers-augmented2
  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-numbers-augmented2

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: 0.1392
- Accuracy: 0.9681
- F1: 0.9680
- Precision: 0.9692
- Recall: 0.9678

## 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: 6756

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.3906        | 0.0833  | 563  | 1.2362          | 0.5628   | 0.5561 | 0.6171    | 0.5623 |
| 0.7242        | 1.0833  | 1126 | 0.8677          | 0.6867   | 0.6787 | 0.7247    | 0.6847 |
| 0.5625        | 2.0833  | 1689 | 0.6211          | 0.7883   | 0.7865 | 0.8163    | 0.7871 |
| 0.5111        | 3.0833  | 2252 | 0.4169          | 0.8623   | 0.8621 | 0.8814    | 0.8631 |
| 0.1224        | 4.0833  | 2815 | 0.2908          | 0.9036   | 0.9030 | 0.9077    | 0.9038 |
| 0.0561        | 5.0833  | 3378 | 0.2836          | 0.9208   | 0.9207 | 0.9252    | 0.9210 |
| 0.0028        | 6.0833  | 3941 | 0.2256          | 0.9466   | 0.9470 | 0.9488    | 0.9471 |
| 0.0009        | 7.0833  | 4504 | 0.1670          | 0.9673   | 0.9676 | 0.9702    | 0.9665 |
| 0.0336        | 8.0833  | 5067 | 0.1362          | 0.9656   | 0.9656 | 0.9674    | 0.9650 |
| 0.0004        | 9.0833  | 5630 | 0.1192          | 0.9776   | 0.9778 | 0.9793    | 0.9771 |
| 0.0004        | 10.0833 | 6193 | 0.1204          | 0.9725   | 0.9725 | 0.9745    | 0.9719 |
| 0.0003        | 11.0833 | 6756 | 0.1268          | 0.9725   | 0.9723 | 0.9738    | 0.9719 |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1