---
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: 1.4025
- Accuracy: 0.2237

## 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-06
- train_batch_size: 8
- eval_batch_size: 8
- 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: 480

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3855        | 1.0   | 25   | 1.3973          | 0.275    |
| 1.4151        | 2.0   | 50   | 1.4034          | 0.1875   |
| 1.4342        | 3.0   | 75   | 1.4028          | 0.2      |
| 1.4189        | 4.0   | 100  | 1.3967          | 0.1625   |
| 1.3925        | 5.0   | 125  | 1.4030          | 0.2375   |
| 1.406         | 6.0   | 150  | 1.3974          | 0.1875   |
| 1.3868        | 7.0   | 175  | 1.4011          | 0.175    |
| 1.3969        | 8.0   | 200  | 1.4019          | 0.15     |
| 1.4233        | 9.0   | 225  | 1.3985          | 0.2125   |
| 1.4011        | 10.0  | 250  | 1.4081          | 0.25     |
| 1.3994        | 11.0  | 275  | 1.4037          | 0.175    |
| 1.3945        | 12.0  | 300  | 1.4094          | 0.2625   |
| 1.3844        | 13.0  | 325  | 1.4050          | 0.175    |
| 1.378         | 14.0  | 350  | 1.4081          | 0.275    |
| 1.3965        | 15.0  | 375  | 1.4095          | 0.275    |
| 1.3982        | 16.0  | 400  | 1.4116          | 0.275    |
| 1.385         | 17.0  | 425  | 1.4114          | 0.275    |
| 1.3735        | 18.0  | 450  | 1.4103          | 0.275    |
| 1.3817        | 19.0  | 475  | 1.4106          | 0.275    |
| 1.3785        | 19.2  | 480  | 1.4106          | 0.275    |


### Framework versions

- Transformers 4.44.1
- Pytorch 2.4.0
- Datasets 2.19.1
- Tokenizers 0.19.1