---
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: 3.0235
- Accuracy: 0.2575

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 480

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 4.2682        | 0.0646  | 31   | 4.2493          | 0.0033   |
| 4.2584        | 1.0646  | 62   | 4.2434          | 0.0134   |
| 4.2518        | 2.0646  | 93   | 4.2246          | 0.0167   |
| 4.2445        | 3.0646  | 124  | 4.2208          | 0.0067   |
| 4.2272        | 4.0646  | 155  | 4.2230          | 0.0100   |
| 4.205         | 5.0646  | 186  | 4.2111          | 0.0234   |
| 4.1238        | 6.0646  | 217  | 4.1112          | 0.0368   |
| 3.9136        | 7.0646  | 248  | 3.8530          | 0.0736   |
| 3.6241        | 8.0646  | 279  | 3.6734          | 0.1171   |
| 3.3103        | 9.0646  | 310  | 3.5261          | 0.1070   |
| 3.0981        | 10.0646 | 341  | 3.3860          | 0.1639   |
| 2.8216        | 11.0646 | 372  | 3.1791          | 0.2140   |
| 2.6108        | 12.0646 | 403  | 3.1618          | 0.2441   |
| 2.598         | 13.0646 | 434  | 3.0793          | 0.2341   |
| 2.5023        | 14.0646 | 465  | 3.0194          | 0.2575   |
| 2.513         | 15.0312 | 480  | 3.0668          | 0.2375   |


### Framework versions

- Transformers 4.48.0
- Pytorch 2.5.1+cu118
- Datasets 3.2.0
- Tokenizers 0.21.0