---
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-colab
  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-colab

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: 0.3187
- Accuracy: 0.9237

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5766        | 0.09  | 188  | 0.7504          | 0.7956   |
| 0.4124        | 1.09  | 376  | 0.4797          | 0.8638   |
| 0.104         | 2.09  | 564  | 0.5037          | 0.8583   |
| 0.0652        | 3.09  | 752  | 0.5683          | 0.8556   |
| 0.0821        | 4.09  | 940  | 0.4314          | 0.8992   |
| 0.0015        | 5.09  | 1128 | 0.5824          | 0.8883   |
| 0.0024        | 6.09  | 1316 | 0.4310          | 0.8883   |
| 0.0007        | 7.09  | 1504 | 0.4375          | 0.8992   |
| 0.0007        | 8.09  | 1692 | 0.3199          | 0.9183   |
| 0.0006        | 9.09  | 1880 | 0.3189          | 0.9210   |
| 0.0006        | 10.09 | 2057 | 0.3187          | 0.9237   |


### Framework versions

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