---
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: 0.4448
- Accuracy: 0.8452

## 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: 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: 148

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 2.3498        | 0.1284 | 19   | 2.0894          | 0.2143   |
| 1.9304        | 1.1284 | 38   | 1.5131          | 0.4857   |
| 1.099         | 2.1284 | 57   | 0.8322          | 0.6857   |
| 0.4725        | 3.1284 | 76   | 0.5528          | 0.7714   |
| 0.3629        | 4.1284 | 95   | 0.3822          | 0.8571   |
| 0.196         | 5.1284 | 114  | 0.3011          | 0.9143   |
| 0.1357        | 6.1284 | 133  | 0.2539          | 0.9143   |
| 0.0847        | 7.1014 | 148  | 0.1923          | 0.9429   |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0