---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-elderf1
  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-elderf1

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: 1.7031
- Accuracy: 0.3481

## 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: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- 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: 720

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7358        | 0.1   | 73   | 1.6923          | 0.3408   |
| 1.7163        | 1.1   | 146  | 1.6662          | 0.3373   |
| 1.7018        | 2.1   | 219  | 1.6378          | 0.3408   |
| 1.7334        | 3.1   | 292  | 1.6563          | 0.3401   |
| 1.672         | 4.1   | 365  | 1.6568          | 0.2398   |
| 1.7095        | 5.1   | 438  | 1.6313          | 0.3387   |
| 1.7119        | 6.1   | 511  | 1.6309          | 0.3408   |
| 1.6981        | 7.1   | 584  | 1.6518          | 0.3289   |
| 1.7066        | 8.1   | 657  | 1.6313          | 0.3310   |
| 1.6476        | 9.09  | 720  | 1.6338          | 0.3289   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2