---
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-custom-subset
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/huangyangyu/huggingface/runs/v8zohmjq)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/huangyangyu/huggingface/runs/v8zohmjq)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/huangyangyu/huggingface/runs/v8zohmjq)
# videomae-base-finetuned-kinetics-finetuned-custom-subset

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: 0.9783
- Accuracy: 0.7564

## 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: 5e-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: 710

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.6747        | 0.1014 | 72   | 0.6989          | 0.7308   |
| 0.5585        | 1.1014 | 144  | 0.7504          | 0.7308   |
| 1.0181        | 2.1014 | 216  | 0.5370          | 0.6795   |
| 0.5883        | 3.1014 | 288  | 0.6710          | 0.7308   |
| 0.3918        | 4.1014 | 360  | 0.5803          | 0.7692   |
| 0.3903        | 5.1014 | 432  | 0.5857          | 0.7436   |
| 0.2452        | 6.1014 | 504  | 0.8492          | 0.7308   |
| 0.4107        | 7.1014 | 576  | 0.8475          | 0.7308   |
| 0.099         | 8.1014 | 648  | 0.9360          | 0.7436   |
| 0.0679        | 9.0873 | 710  | 0.9783          | 0.7564   |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.1.1
- Datasets 2.13.2
- Tokenizers 0.19.1