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---
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
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