---
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-final-contest-baole4-0705
  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-final-contest-baole4-0705

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: 0.3771
- Accuracy: 0.8807

## 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: 1e-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: 2805

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.4477        | 0.0670  | 188  | 0.8428          | 0.8486   |
| 0.3123        | 1.0670  | 376  | 0.6401          | 0.8532   |
| 0.2498        | 2.0670  | 564  | 0.5204          | 0.8578   |
| 0.0348        | 3.0670  | 752  | 0.4130          | 0.8899   |
| 0.146         | 4.0670  | 940  | 0.3617          | 0.8991   |
| 0.038         | 5.0670  | 1128 | 0.4519          | 0.8670   |
| 0.0116        | 6.0670  | 1316 | 0.4160          | 0.8716   |
| 0.0083        | 7.0670  | 1504 | 0.3683          | 0.8807   |
| 0.0067        | 8.0670  | 1692 | 0.3820          | 0.8807   |
| 0.0051        | 9.0670  | 1880 | 0.3932          | 0.8761   |
| 0.0057        | 10.0670 | 2068 | 0.3944          | 0.8853   |
| 0.0045        | 11.0670 | 2256 | 0.4133          | 0.8761   |
| 0.0042        | 12.0670 | 2444 | 0.3813          | 0.8807   |
| 0.0037        | 13.0670 | 2632 | 0.3806          | 0.8853   |
| 0.0039        | 14.0617 | 2805 | 0.3771          | 0.8807   |


### Framework versions

- Transformers 4.40.2
- Pytorch 1.13.1+cu117
- Datasets 2.18.0
- Tokenizers 0.19.1