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

This model is a fine-tuned version of [MCG-NJU/videomae-base-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-base-finetuned-kinetics) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6795
- Accuracy: 0.8458

## 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: 9e-05
- train_batch_size: 4
- eval_batch_size: 4
- 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: 2464

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.0054        | 0.0913  | 225  | 0.9635          | 0.7764   |
| 0.3981        | 1.0913  | 450  | 0.7286          | 0.7747   |
| 0.1595        | 2.0913  | 675  | 0.6008          | 0.8215   |
| 0.0302        | 3.0913  | 900  | 0.7152          | 0.8024   |
| 0.015         | 4.0913  | 1125 | 0.7613          | 0.7903   |
| 0.0019        | 5.0913  | 1350 | 0.6450          | 0.8354   |
| 0.0037        | 6.0913  | 1575 | 0.5948          | 0.8510   |
| 0.0037        | 7.0913  | 1800 | 0.6545          | 0.8354   |
| 0.0005        | 8.0913  | 2025 | 0.6526          | 0.8440   |
| 0.0005        | 9.0913  | 2250 | 0.6803          | 0.8458   |
| 0.0004        | 10.0869 | 2464 | 0.6795          | 0.8458   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1