---
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: 0.8198
- Accuracy: 0.8298

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.01  | 300  | 2.3345          | 0.4887   |
| No log        | 2.01  | 600  | 1.4956          | 0.6433   |
| No log        | 3.01  | 900  | 1.1647          | 0.7162   |
| 1.5784        | 4.01  | 1200 | 1.1531          | 0.7029   |
| 1.5784        | 5.01  | 1500 | 1.0251          | 0.7334   |
| 1.5784        | 6.01  | 1800 | 1.0315          | 0.7333   |
| 0.1821        | 7.01  | 2100 | 0.9787          | 0.7617   |
| 0.1821        | 8.01  | 2400 | 0.8933          | 0.7838   |
| 0.1821        | 9.01  | 2700 | 0.8781          | 0.7917   |
| 0.0651        | 10.01 | 3000 | 0.9051          | 0.7910   |
| 0.0651        | 11.01 | 3300 | 0.9593          | 0.7900   |
| 0.0651        | 12.01 | 3600 | 0.8054          | 0.8187   |
| 0.0651        | 13.01 | 3900 | 0.8679          | 0.8142   |
| 0.0265        | 14.01 | 4200 | 0.8380          | 0.8208   |
| 0.0265        | 15.01 | 4500 | 0.8317          | 0.8247   |
| 0.0265        | 16.01 | 4800 | 0.8027          | 0.8249   |
| 0.0091        | 17.01 | 5100 | 0.8240          | 0.8255   |
| 0.0091        | 18.01 | 5400 | 0.8480          | 0.8211   |
| 0.0091        | 19.01 | 5700 | 0.8198          | 0.8298   |
| 0.0091        | 19.87 | 5960 | 0.8315          | 0.8283   |


### Framework versions

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