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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-midv-holo-500
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-midv-holo-500
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: 2.8322
- Accuracy: 0.4264
## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.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: 0.1
- training_steps: 1925
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.2647 | 0.0405 | 78 | 1.2009 | 0.5736 |
| 1.3169 | 1.0405 | 156 | 1.2652 | 0.5078 |
| 1.3004 | 2.0405 | 234 | 1.2036 | 0.5736 |
| 1.1562 | 3.0405 | 312 | 1.1888 | 0.5736 |
| 1.265 | 4.0405 | 390 | 1.2808 | 0.4922 |
| 1.1946 | 5.0405 | 468 | 1.3394 | 0.3295 |
| 1.1222 | 6.0405 | 546 | 1.3204 | 0.5 |
| 1.0244 | 7.0405 | 624 | 1.3697 | 0.3643 |
| 1.1604 | 8.0405 | 702 | 1.3813 | 0.4535 |
| 0.8901 | 9.0405 | 780 | 1.4395 | 0.4225 |
| 0.6032 | 10.0405 | 858 | 1.6609 | 0.4535 |
| 0.6889 | 11.0405 | 936 | 1.7041 | 0.3605 |
| 0.5777 | 12.0405 | 1014 | 1.9075 | 0.3915 |
| 0.4317 | 13.0405 | 1092 | 1.6528 | 0.4690 |
| 0.5087 | 14.0405 | 1170 | 1.6126 | 0.4845 |
| 0.1257 | 15.0405 | 1248 | 2.0637 | 0.4147 |
| 0.3774 | 16.0405 | 1326 | 2.5347 | 0.3721 |
| 0.1259 | 17.0405 | 1404 | 2.6514 | 0.3760 |
| 0.2158 | 18.0405 | 1482 | 2.4290 | 0.4806 |
| 0.0505 | 19.0405 | 1560 | 2.6998 | 0.4225 |
| 0.0563 | 20.0405 | 1638 | 2.6474 | 0.4225 |
| 0.0671 | 21.0405 | 1716 | 2.6487 | 0.4496 |
| 0.1847 | 22.0405 | 1794 | 2.7012 | 0.4496 |
| 0.0041 | 23.0405 | 1872 | 2.7938 | 0.4341 |
| 0.0079 | 24.0275 | 1925 | 2.8322 | 0.4264 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu118
- Datasets 3.2.0
- Tokenizers 0.21.0
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