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---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-slrbd002
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-slrbd002
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: 0.4824
- Accuracy: 0.875
## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 1800
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.6684 | 0.05 | 90 | 3.6696 | 0.025 |
| 3.4781 | 1.05 | 180 | 3.3494 | 0.1313 |
| 3.2885 | 2.05 | 270 | 3.1702 | 0.125 |
| 2.7847 | 3.05 | 360 | 2.7654 | 0.2562 |
| 2.4107 | 4.05 | 450 | 2.6756 | 0.2437 |
| 1.7783 | 5.05 | 540 | 1.9950 | 0.4813 |
| 1.3054 | 6.05 | 630 | 1.4908 | 0.6188 |
| 0.5868 | 7.05 | 720 | 1.4568 | 0.6188 |
| 0.4388 | 8.05 | 810 | 0.9511 | 0.7312 |
| 0.2187 | 9.05 | 900 | 1.1580 | 0.65 |
| 0.1665 | 10.05 | 990 | 0.6565 | 0.8313 |
| 0.0959 | 11.05 | 1080 | 0.5731 | 0.8562 |
| 0.0273 | 12.05 | 1170 | 0.6637 | 0.8063 |
| 0.02 | 13.05 | 1260 | 0.5048 | 0.875 |
| 0.0137 | 14.05 | 1350 | 0.4815 | 0.8688 |
| 0.0261 | 15.05 | 1440 | 0.5649 | 0.8438 |
| 0.013 | 16.05 | 1530 | 0.5419 | 0.8375 |
| 0.0123 | 17.05 | 1620 | 0.4864 | 0.8812 |
| 0.0527 | 18.05 | 1710 | 0.4725 | 0.8875 |
| 0.011 | 19.05 | 1800 | 0.4824 | 0.875 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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