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---
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
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