---
library_name: transformers
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-allkisa-0219
  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-allkisa-0219

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: 0.3020
- Accuracy: 0.9394

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 7840

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.0617        | 0.0251  | 197  | 0.3995          | 0.8433   |
| 0.0008        | 1.0251  | 394  | 0.3034          | 0.8715   |
| 0.0006        | 2.0251  | 591  | 0.3897          | 0.8762   |
| 1.2877        | 3.0251  | 788  | 0.3241          | 0.8809   |
| 0.0024        | 4.0251  | 985  | 0.3393          | 0.8856   |
| 0.0002        | 5.0251  | 1182 | 0.3336          | 0.9013   |
| 0.0005        | 6.0251  | 1379 | 0.4018          | 0.9028   |
| 0.0001        | 7.0251  | 1576 | 0.4943          | 0.8966   |
| 0.0004        | 8.0251  | 1773 | 0.6253          | 0.8323   |
| 0.0003        | 9.0251  | 1970 | 0.3540          | 0.9075   |
| 0.0005        | 10.0251 | 2167 | 0.4543          | 0.9013   |
| 0.0003        | 11.0251 | 2364 | 0.6340          | 0.8746   |
| 0.0           | 12.0251 | 2561 | 0.4580          | 0.9028   |
| 0.0004        | 13.0251 | 2758 | 0.5239          | 0.8997   |
| 0.0003        | 14.0251 | 2955 | 0.4695          | 0.9028   |
| 0.0025        | 15.0251 | 3152 | 0.6634          | 0.8762   |
| 0.0001        | 16.0251 | 3349 | 0.5013          | 0.9075   |
| 0.0           | 17.0251 | 3546 | 0.4318          | 0.9216   |
| 0.0001        | 18.0251 | 3743 | 0.4857          | 0.9169   |
| 0.0001        | 19.0251 | 3940 | 0.4436          | 0.9138   |
| 0.0002        | 20.0251 | 4137 | 0.5982          | 0.8950   |
| 0.0059        | 21.0251 | 4334 | 0.4260          | 0.9248   |
| 0.0376        | 22.0251 | 4531 | 0.4158          | 0.9263   |
| 0.0           | 23.0251 | 4728 | 0.4742          | 0.9169   |
| 0.0           | 24.0251 | 4925 | 0.4715          | 0.9107   |
| 0.0002        | 25.0251 | 5122 | 0.4703          | 0.9044   |
| 0.0004        | 26.0251 | 5319 | 0.4396          | 0.9138   |
| 0.0001        | 27.0251 | 5516 | 0.4424          | 0.9201   |
| 0.0           | 28.0251 | 5713 | 0.4931          | 0.8966   |
| 0.0001        | 29.0251 | 5910 | 0.5090          | 0.9028   |
| 0.0001        | 30.0251 | 6107 | 0.5055          | 0.9028   |
| 0.0           | 31.0251 | 6304 | 0.5457          | 0.8934   |
| 0.0227        | 32.0251 | 6501 | 0.5026          | 0.9013   |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0