---
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: 0.0000
- Accuracy: 1.0
- Precision: 1.0
- Recall: 1.0
- F1: 1.0

## 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: 12850

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.5601        | 1.0     | 515   | 0.4608          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.6361        | 2.0     | 1030  | 2.9149          | 0.0      | 0.0       | 0.0    | 0.0    |
| 0.1473        | 3.0     | 1545  | 0.0617          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.0012        | 4.0     | 2060  | 0.0004          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.096         | 5.0     | 2575  | 0.0004          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.1104        | 6.0     | 3090  | 0.0003          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.2175        | 7.0     | 3605  | 2.6599          | 0.6667   | 1.0       | 0.6667 | 0.8000 |
| 0.0004        | 8.0     | 4120  | 0.0003          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.1348        | 9.0     | 4635  | 0.0011          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.0001        | 10.0    | 5150  | 0.0001          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.1291        | 11.0    | 5665  | 0.0001          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.174         | 12.0    | 6180  | 0.0002          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.0002        | 13.0    | 6695  | 0.0019          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.0001        | 14.0    | 7210  | 0.0000          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.0           | 15.0    | 7725  | 0.0000          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.0           | 16.0    | 8240  | 0.0000          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.0           | 17.0    | 8755  | 0.0000          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.0           | 18.0    | 9270  | 0.0000          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.0           | 19.0    | 9785  | 0.0000          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.0           | 20.0    | 10300 | 0.0000          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.0           | 21.0    | 10815 | 0.0000          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.0           | 22.0    | 11330 | 0.0000          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.0           | 23.0    | 11845 | 0.0000          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.0           | 24.0    | 12360 | 0.0000          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.0           | 24.9515 | 12850 | 0.0000          | 1.0      | 1.0       | 1.0    | 1.0    |


### Framework versions

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