---
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: 0.5324
- Accuracy: 0.7871

## 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: 16
- eval_batch_size: 16
- 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: 148

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.3271        | 0.13  | 19   | 2.1350          | 0.2429   |
| 1.9566        | 1.13  | 38   | 1.4260          | 0.5857   |
| 1.0941        | 2.13  | 57   | 0.8857          | 0.7143   |
| 0.5363        | 3.13  | 76   | 0.6664          | 0.7143   |
| 0.3392        | 4.13  | 95   | 0.4023          | 0.9143   |
| 0.1765        | 5.13  | 114  | 0.3487          | 0.9      |
| 0.1318        | 6.13  | 133  | 0.3181          | 0.9      |
| 0.1092        | 7.1   | 148  | 0.2886          | 0.9      |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.1