---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-large-finetuned-kinetics
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: MAE-CT-CPC-Dicotomized-v4-early-stop
  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. -->

# MAE-CT-CPC-Dicotomized-v4-early-stop

This model is a fine-tuned version of [MCG-NJU/videomae-large-finetuned-kinetics](https://huggingface.co./MCG-NJU/videomae-large-finetuned-kinetics) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4282
- Accuracy: 0.8293

## 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: 1440

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5342        | 0.06  | 81   | 0.6496          | 0.6829   |
| 0.6266        | 1.06  | 162  | 0.5854          | 0.6829   |
| 0.6599        | 2.06  | 243  | 0.5206          | 0.6829   |
| 0.877         | 3.06  | 324  | 0.5995          | 0.6098   |
| 0.653         | 4.06  | 405  | 0.4908          | 0.7561   |
| 0.7604        | 5.06  | 486  | 0.4936          | 0.7805   |
| 0.4795        | 6.06  | 567  | 0.9528          | 0.6829   |
| 0.278         | 7.06  | 648  | 0.5565          | 0.8049   |
| 0.3548        | 8.06  | 729  | 0.5855          | 0.7561   |
| 0.4386        | 9.06  | 810  | 0.6578          | 0.7561   |
| 0.3007        | 10.06 | 891  | 0.6622          | 0.7805   |
| 0.313         | 11.06 | 972  | 0.8350          | 0.7561   |
| 0.0554        | 12.06 | 1053 | 1.0043          | 0.7073   |
| 0.2804        | 13.06 | 1134 | 1.0247          | 0.7073   |
| 0.1424        | 14.06 | 1215 | 0.8542          | 0.7805   |
| 0.4692        | 15.06 | 1296 | 1.0264          | 0.7317   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.0.1+cu117
- Datasets 3.0.1
- Tokenizers 0.15.1