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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-groub1-finetuned-SLT-subset
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-groub1-finetuned-SLT-subset
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: 0.3056
- Accuracy: 0.9767
## 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: 2
- eval_batch_size: 2
- 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: 1008
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.8889 | 0.06 | 64 | 3.6733 | 0.0465 |
| 3.8474 | 1.06 | 128 | 3.7358 | 0.0698 |
| 3.7886 | 2.06 | 192 | 3.6336 | 0.0465 |
| 3.7398 | 3.06 | 256 | 3.5894 | 0.0698 |
| 3.7363 | 4.06 | 320 | 3.4637 | 0.0698 |
| 3.6345 | 5.06 | 384 | 3.3875 | 0.0698 |
| 3.2723 | 6.06 | 448 | 3.2156 | 0.1163 |
| 3.2814 | 7.06 | 512 | 2.7291 | 0.7209 |
| 2.7245 | 8.06 | 576 | 1.9657 | 0.8140 |
| 1.8616 | 9.06 | 640 | 1.2883 | 0.8837 |
| 1.3802 | 10.06 | 704 | 0.8116 | 0.9302 |
| 1.0416 | 11.06 | 768 | 0.5877 | 0.9535 |
| 0.6415 | 12.06 | 832 | 0.4426 | 0.9767 |
| 0.5546 | 13.06 | 896 | 0.3599 | 0.9767 |
| 0.4495 | 14.06 | 960 | 0.3212 | 0.9767 |
| 0.2214 | 15.05 | 1008 | 0.3056 | 0.9767 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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