---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- video-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ucf101_42
  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. -->

# ucf101_42

This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on the ucf101 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8124
- Accuracy: 0.7958
- Test Accuracy: 0.7958
- Df Accuracy: 0.9353
- Unlearn Overall Accuracy: 0.4302
- Unlearn Time: 4452.2733

## 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: 8
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Overall Accuracy | Unlearn Overall Accuracy | Time |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----------------:|:------------------------:|:----:|
| No log        | 1.01  | 300  | 0.8241          | 0.9538   | 0.4216           | 0.4216                   | -1   |
| No log        | 2.01  | 600  | 1.0017          | 0.8892   | 0.4249           | 0.4249                   | -1   |
| No log        | 2.99  | 894  | 0.8121          | 0.9353   | 0.4302           | 0.4302                   | -1   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2