---
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
  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

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: 0.3433
- Accuracy: 0.8222
- F1: 0.8015
- Precision: 0.8762
- Recall: 0.8182

## 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: 176

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.7592        | 0.25  | 44   | 0.6378          | 0.8462   | 0.8479 | 0.8758    | 0.8561 |
| 0.296         | 1.25  | 88   | 0.3027          | 0.8974   | 0.8805 | 0.9091    | 0.8864 |
| 0.2144        | 2.25  | 132  | 0.1289          | 0.9487   | 0.9377 | 0.9545    | 0.9394 |
| 0.1331        | 3.25  | 176  | 0.0958          | 0.9744   | 0.9688 | 0.9773    | 0.9697 |


### Framework versions

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