---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base-finetuned-kinetics
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-finetuned
  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-finetuned

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: 0.1289
- Accuracy: 0.9706

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- training_steps: 8620

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7657        | 0.05  | 432  | 0.6104          | 0.8243   |
| 0.4011        | 1.05  | 864  | 0.4283          | 0.8896   |
| 0.301         | 2.05  | 1296 | 0.3957          | 0.8833   |
| 0.2967        | 3.05  | 1728 | 0.3066          | 0.9138   |
| 0.229         | 4.05  | 2160 | 0.3268          | 0.9092   |
| 0.2185        | 5.05  | 2592 | 0.2865          | 0.9281   |
| 0.1863        | 6.05  | 3024 | 0.2550          | 0.9320   |
| 0.1386        | 7.05  | 3456 | 0.2366          | 0.9422   |
| 0.1542        | 8.05  | 3888 | 0.2162          | 0.9449   |
| 0.1396        | 9.05  | 4320 | 0.2069          | 0.9424   |
| 0.1323        | 10.05 | 4752 | 0.2021          | 0.9486   |
| 0.1008        | 11.05 | 5184 | 0.2408          | 0.9465   |
| 0.0756        | 12.05 | 5616 | 0.2023          | 0.9509   |
| 0.0628        | 13.05 | 6048 | 0.1730          | 0.9609   |
| 0.0747        | 14.05 | 6480 | 0.1747          | 0.9622   |
| 0.047         | 15.05 | 6912 | 0.1698          | 0.9629   |
| 0.0586        | 16.05 | 7344 | 0.1412          | 0.9668   |
| 0.0644        | 17.05 | 7776 | 0.1314          | 0.9704   |
| 0.0521        | 18.05 | 8208 | 0.1343          | 0.9688   |
| 0.0516        | 19.05 | 8620 | 0.1289          | 0.9706   |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.0.1+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2