---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-sphar
  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-sphar

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: 0.9060
- Accuracy: 0.7428

## 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: 2
- eval_batch_size: 2
- 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: 3752

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.1838        | 0.2463 | 924  | 1.1104          | 0.7292   |
| 1.0275        | 1.2463 | 1848 | 0.9165          | 0.7214   |
| 0.6294        | 2.2463 | 2772 | 0.9556          | 0.7409   |
| 1.2754        | 3.2463 | 3696 | 0.9022          | 0.7444   |
| 0.6501        | 4.0149 | 3752 | 0.9060          | 0.7428   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1