---
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: 0.0794
- Accuracy: 0.9714

## 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: 6
- eval_batch_size: 6
- 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: 600

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 2.1779        | 0.0833  | 50   | 2.0389          | 0.2714   |
| 0.9209        | 1.0833  | 100  | 0.9262          | 0.6857   |
| 0.5527        | 2.0833  | 150  | 0.3633          | 0.9143   |
| 0.2367        | 3.0833  | 200  | 0.4540          | 0.8857   |
| 0.4635        | 4.0833  | 250  | 0.2192          | 0.9429   |
| 0.097         | 5.0833  | 300  | 0.2792          | 0.8714   |
| 0.0128        | 6.0833  | 350  | 0.1230          | 0.9571   |
| 0.0346        | 7.0833  | 400  | 0.0637          | 0.9714   |
| 0.005         | 8.0833  | 450  | 0.0655          | 0.9714   |
| 0.0045        | 9.0833  | 500  | 0.0876          | 0.9714   |
| 0.004         | 10.0833 | 550  | 0.0904          | 0.9714   |
| 0.0041        | 11.0833 | 600  | 0.0794          | 0.9714   |


### Framework versions

- Transformers 4.45.1
- Pytorch 1.13.1+cu117
- Datasets 3.0.1
- Tokenizers 0.20.0