---
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: 0.4681
- Accuracy: 0.7907

## 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: 3500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6769        | 0.02  | 70   | 0.6814          | 0.5938   |
| 0.7223        | 1.02  | 140  | 0.6953          | 0.5938   |
| 0.6628        | 2.02  | 210  | 0.6335          | 0.625    |
| 0.5096        | 3.02  | 280  | 0.6514          | 0.625    |
| 0.4739        | 4.02  | 350  | 0.6358          | 0.6562   |
| 0.4554        | 5.02  | 420  | 0.6272          | 0.6562   |
| 0.4818        | 6.02  | 490  | 0.7727          | 0.5938   |
| 0.4129        | 7.02  | 560  | 0.8222          | 0.6875   |
| 0.6301        | 8.02  | 630  | 0.8041          | 0.625    |
| 0.3809        | 9.02  | 700  | 0.8721          | 0.625    |
| 0.8071        | 10.02 | 770  | 1.1092          | 0.625    |
| 0.1888        | 11.02 | 840  | 1.1556          | 0.625    |
| 0.3762        | 12.02 | 910  | 1.3499          | 0.625    |
| 0.3502        | 13.02 | 980  | 1.5333          | 0.6562   |
| 0.1027        | 14.02 | 1050 | 1.6249          | 0.6562   |
| 0.177         | 15.02 | 1120 | 1.3758          | 0.6562   |
| 0.0998        | 16.02 | 1190 | 1.9514          | 0.6562   |
| 0.1749        | 17.02 | 1260 | 1.9120          | 0.6562   |
| 0.0145        | 18.02 | 1330 | 2.1036          | 0.625    |
| 0.0038        | 19.02 | 1400 | 2.0288          | 0.625    |
| 0.1262        | 20.02 | 1470 | 2.0193          | 0.6875   |
| 0.0203        | 21.02 | 1540 | 2.1937          | 0.6562   |
| 0.0002        | 22.02 | 1610 | 2.2922          | 0.625    |
| 0.0017        | 23.02 | 1680 | 2.1569          | 0.6562   |
| 0.0049        | 24.02 | 1750 | 2.2573          | 0.625    |
| 0.0231        | 25.02 | 1820 | 2.1460          | 0.6875   |
| 0.0001        | 26.02 | 1890 | 2.3566          | 0.6562   |
| 0.0001        | 27.02 | 1960 | 2.3822          | 0.5938   |
| 0.0001        | 28.02 | 2030 | 2.3178          | 0.6562   |
| 0.0004        | 29.02 | 2100 | 2.5492          | 0.625    |
| 0.0003        | 30.02 | 2170 | 2.7648          | 0.625    |
| 0.0001        | 31.02 | 2240 | 2.3949          | 0.625    |
| 0.0001        | 32.02 | 2310 | 2.4107          | 0.6562   |
| 0.0001        | 33.02 | 2380 | 2.6099          | 0.5938   |
| 0.0001        | 34.02 | 2450 | 2.8574          | 0.5625   |
| 0.0001        | 35.02 | 2520 | 2.5808          | 0.5938   |
| 0.0001        | 36.02 | 2590 | 2.6246          | 0.5938   |
| 0.0001        | 37.02 | 2660 | 2.7051          | 0.5938   |
| 0.0001        | 38.02 | 2730 | 2.5046          | 0.5938   |
| 0.0001        | 39.02 | 2800 | 2.5003          | 0.5938   |
| 0.0           | 40.02 | 2870 | 2.5460          | 0.625    |
| 0.0           | 41.02 | 2940 | 2.5397          | 0.625    |
| 0.0           | 42.02 | 3010 | 2.5384          | 0.625    |
| 0.0           | 43.02 | 3080 | 2.4849          | 0.625    |
| 0.0           | 44.02 | 3150 | 2.5847          | 0.6562   |
| 0.0           | 45.02 | 3220 | 2.5829          | 0.6562   |
| 0.0           | 46.02 | 3290 | 2.5809          | 0.6562   |
| 0.0           | 47.02 | 3360 | 2.5756          | 0.625    |
| 0.0001        | 48.02 | 3430 | 2.4744          | 0.6562   |
| 0.0           | 49.02 | 3500 | 2.4720          | 0.6562   |


### Framework versions

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