---
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-baole3-0705
  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-baole3-0705

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: 0.3846
- Accuracy: 0.9083

## 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: 2057

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.7136        | 0.0914  | 188  | 0.9178          | 0.7615   |
| 0.0707        | 1.0914  | 376  | 0.5263          | 0.8303   |
| 0.1033        | 2.0914  | 564  | 0.4823          | 0.8670   |
| 0.0055        | 3.0914  | 752  | 0.4533          | 0.8945   |
| 0.0295        | 4.0914  | 940  | 0.4714          | 0.8807   |
| 0.0011        | 5.0914  | 1128 | 0.4415          | 0.8853   |
| 0.0013        | 6.0914  | 1316 | 0.4121          | 0.8853   |
| 0.0007        | 7.0914  | 1504 | 0.4474          | 0.8945   |
| 0.0008        | 8.0914  | 1692 | 0.3972          | 0.9083   |
| 0.0006        | 9.0914  | 1880 | 0.3841          | 0.9083   |
| 0.0005        | 10.0860 | 2057 | 0.3846          | 0.9083   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1