---
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-finetuned-data-no-yolo-kaggle
  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-finetuned-data-no-yolo-kaggle

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: 0.4866
- Accuracy: 0.9046

## 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: 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: 4125

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2716        | 0.09  | 376  | 0.6657          | 0.8147   |
| 0.2248        | 1.09  | 752  | 0.5673          | 0.8065   |
| 0.0106        | 2.09  | 1128 | 0.4900          | 0.8529   |
| 0.0548        | 3.09  | 1504 | 0.5760          | 0.8719   |
| 0.0203        | 4.09  | 1880 | 0.8674          | 0.8311   |
| 0.0008        | 5.09  | 2256 | 0.5422          | 0.8692   |
| 0.0004        | 6.09  | 2632 | 0.4938          | 0.8965   |
| 0.0021        | 7.09  | 3008 | 0.7053          | 0.8583   |
| 0.0002        | 8.09  | 3384 | 0.5675          | 0.8747   |
| 0.0003        | 9.09  | 3760 | 0.4930          | 0.9046   |
| 0.0003        | 10.09 | 4125 | 0.4866          | 0.9046   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2