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---
library_name: transformers
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-kisa
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. -->
# videomae-base-finetuned-kisa
This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.2647
- Accuracy: 0.4913
## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 2725
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.0741 | 0.0404 | 110 | 1.1353 | 0.5 |
| 0.0259 | 1.0404 | 220 | 3.7142 | 0.1183 |
| 0.5784 | 2.0404 | 330 | 2.2692 | 0.5 |
| 0.1384 | 3.0404 | 440 | 1.3726 | 0.5178 |
| 0.513 | 4.0404 | 550 | 2.5340 | 0.3728 |
| 0.0156 | 5.0404 | 660 | 2.3487 | 0.2041 |
| 0.0033 | 6.0404 | 770 | 4.4601 | 0.1953 |
| 0.0071 | 7.0404 | 880 | 4.6045 | 0.0917 |
| 0.004 | 8.0404 | 990 | 3.4062 | 0.4083 |
| 0.0017 | 9.0404 | 1100 | 2.4961 | 0.4941 |
| 0.4934 | 10.0404 | 1210 | 2.9785 | 0.4941 |
| 0.43 | 11.0404 | 1320 | 3.7030 | 0.5207 |
| 0.0014 | 12.0404 | 1430 | 2.5479 | 0.2012 |
| 0.0021 | 13.0404 | 1540 | 4.0235 | 0.3195 |
| 0.2387 | 14.0404 | 1650 | 4.6049 | 0.2337 |
| 0.0009 | 15.0404 | 1760 | 4.3070 | 0.2485 |
| 0.0004 | 16.0404 | 1870 | 4.4573 | 0.2515 |
| 0.5939 | 17.0404 | 1980 | 4.3423 | 0.3550 |
| 0.0013 | 18.0404 | 2090 | 4.3365 | 0.3047 |
| 0.0015 | 19.0404 | 2200 | 4.0964 | 0.2426 |
| 0.0032 | 20.0404 | 2310 | 4.1795 | 0.2988 |
| 0.0006 | 21.0404 | 2420 | 4.1612 | 0.3136 |
### Framework versions
- Transformers 4.48.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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