---
library_name: transformers
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: 0.6582
- Accuracy: 0.8824

## 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: 488

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.198         | 0.1270 | 62   | 1.4080          | 0.5532   |
| 0.8081        | 1.1270 | 124  | 1.5203          | 0.6596   |
| 0.3909        | 2.1270 | 186  | 1.2482          | 0.7021   |
| 0.2733        | 3.1270 | 248  | 1.1558          | 0.7447   |
| 0.0197        | 4.1270 | 310  | 0.9275          | 0.7660   |
| 0.0911        | 5.1270 | 372  | 1.1365          | 0.7660   |
| 0.0514        | 6.1270 | 434  | 0.7995          | 0.7872   |
| 0.0023        | 7.1107 | 488  | 0.7915          | 0.7872   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1