---
library_name: transformers
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-v8-n0-m1
  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-v8-n0-m1

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: 2.5946
- Accuracy: 0.5753

## 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: 2500

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.6826        | 0.0204  | 51   | 0.6157          | 0.7625   |
| 0.6549        | 1.0204  | 102  | 0.5930          | 0.7625   |
| 0.6486        | 2.0204  | 153  | 0.6797          | 0.5125   |
| 0.5595        | 3.0204  | 204  | 0.4902          | 0.6625   |
| 0.5586        | 4.0204  | 255  | 0.8195          | 0.475    |
| 0.4565        | 5.0204  | 306  | 0.5872          | 0.75     |
| 0.3697        | 6.0204  | 357  | 0.5017          | 0.775    |
| 0.6201        | 7.0204  | 408  | 0.6555          | 0.7      |
| 0.4333        | 8.0204  | 459  | 1.2277          | 0.6125   |
| 0.2148        | 9.0204  | 510  | 0.8115          | 0.7625   |
| 0.9458        | 10.0204 | 561  | 0.9873          | 0.6625   |
| 0.0651        | 11.0204 | 612  | 1.0840          | 0.7625   |
| 0.5756        | 12.0204 | 663  | 1.0489          | 0.8      |
| 0.354         | 13.0204 | 714  | 1.1601          | 0.7875   |
| 0.2888        | 14.0204 | 765  | 1.8144          | 0.625    |
| 0.2449        | 15.0204 | 816  | 1.3988          | 0.7125   |
| 0.1326        | 16.0204 | 867  | 1.7152          | 0.7125   |
| 0.0018        | 17.0204 | 918  | 2.1475          | 0.6375   |
| 0.3631        | 18.0204 | 969  | 1.8957          | 0.65     |
| 0.1252        | 19.0204 | 1020 | 1.1246          | 0.825    |
| 0.0943        | 20.0204 | 1071 | 1.9498          | 0.6625   |
| 0.3488        | 21.0204 | 1122 | 1.3457          | 0.7875   |
| 0.0008        | 22.0204 | 1173 | 1.7872          | 0.7125   |
| 0.009         | 23.0204 | 1224 | 1.5437          | 0.75     |
| 0.0274        | 24.0204 | 1275 | 1.9865          | 0.6875   |
| 0.0004        | 25.0204 | 1326 | 1.5100          | 0.7625   |
| 0.1007        | 26.0204 | 1377 | 1.9590          | 0.6875   |
| 0.0006        | 27.0204 | 1428 | 1.8346          | 0.7125   |
| 0.0006        | 28.0204 | 1479 | 1.4669          | 0.825    |
| 0.0001        | 29.0204 | 1530 | 1.5396          | 0.7875   |
| 0.0002        | 30.0204 | 1581 | 1.5716          | 0.7875   |
| 0.0001        | 31.0204 | 1632 | 1.6614          | 0.7625   |
| 0.0002        | 32.0204 | 1683 | 1.6356          | 0.7625   |
| 0.0001        | 33.0204 | 1734 | 1.5731          | 0.8      |
| 0.0001        | 34.0204 | 1785 | 2.0020          | 0.725    |
| 0.0001        | 35.0204 | 1836 | 1.8886          | 0.75     |
| 0.0001        | 36.0204 | 1887 | 1.8363          | 0.75     |
| 0.0001        | 37.0204 | 1938 | 1.6848          | 0.7625   |
| 0.0001        | 38.0204 | 1989 | 1.7188          | 0.75     |
| 0.0001        | 39.0204 | 2040 | 1.5820          | 0.8      |
| 0.0001        | 40.0204 | 2091 | 1.6061          | 0.7875   |
| 0.0001        | 41.0204 | 2142 | 2.2817          | 0.7      |
| 0.0001        | 42.0204 | 2193 | 2.1015          | 0.725    |
| 0.0001        | 43.0204 | 2244 | 1.6356          | 0.775    |
| 0.0001        | 44.0204 | 2295 | 1.5849          | 0.8125   |
| 0.0001        | 45.0204 | 2346 | 1.6463          | 0.775    |
| 0.0001        | 46.0204 | 2397 | 1.6641          | 0.775    |
| 0.0001        | 47.0204 | 2448 | 1.6123          | 0.7875   |
| 0.0001        | 48.0204 | 2499 | 1.6145          | 0.7875   |
| 0.0001        | 49.0004 | 2500 | 1.6145          | 0.7875   |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.0.1+cu117
- Datasets 3.0.1
- Tokenizers 0.20.0