---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-ucf101-subset
  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-ucf101-subset

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: 0.3585
- Accuracy: 0.9226

## 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: 2
- eval_batch_size: 2
- 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: 3750

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0046        | 0.04  | 150  | 2.0806          | 0.3143   |
| 1.9549        | 1.04  | 300  | 1.4746          | 0.5429   |
| 0.6873        | 2.04  | 450  | 0.9489          | 0.6714   |
| 1.6042        | 3.04  | 600  | 0.6865          | 0.7571   |
| 0.2082        | 4.04  | 750  | 0.4017          | 0.8857   |
| 0.2805        | 5.04  | 900  | 0.9705          | 0.7714   |
| 0.0062        | 6.04  | 1050 | 0.4833          | 0.8571   |
| 0.2727        | 7.04  | 1200 | 0.8048          | 0.8714   |
| 0.1055        | 8.04  | 1350 | 0.0264          | 0.9857   |
| 0.234         | 9.04  | 1500 | 0.1460          | 0.9714   |
| 0.0015        | 10.04 | 1650 | 0.3039          | 0.9429   |
| 0.0012        | 11.04 | 1800 | 0.2351          | 0.9571   |
| 0.0009        | 12.04 | 1950 | 0.3080          | 0.9286   |
| 0.0009        | 13.04 | 2100 | 0.3477          | 0.9429   |
| 0.036         | 14.04 | 2250 | 0.2366          | 0.9571   |
| 0.0008        | 15.04 | 2400 | 0.4506          | 0.9      |
| 0.0037        | 16.04 | 2550 | 0.2327          | 0.9571   |
| 0.0007        | 17.04 | 2700 | 0.3480          | 0.9286   |
| 0.0007        | 18.04 | 2850 | 0.1762          | 0.9714   |
| 0.0006        | 19.04 | 3000 | 0.0991          | 0.9714   |
| 0.0006        | 20.04 | 3150 | 0.1551          | 0.9714   |
| 0.0006        | 21.04 | 3300 | 0.3023          | 0.9429   |
| 0.0006        | 22.04 | 3450 | 0.1543          | 0.9571   |
| 0.0006        | 23.04 | 3600 | 0.1025          | 0.9571   |
| 0.0006        | 24.04 | 3750 | 0.0876          | 0.9571   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3