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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-groub6-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-groub6-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: 2.7184
- Accuracy: 0.1905
## 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: 1
- eval_batch_size: 1
- 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: 132
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.3751 | 0.16 | 21 | 2.9978 | 0.0952 |
| 3.3444 | 1.16 | 42 | 2.9361 | 0.1429 |
| 3.1148 | 2.16 | 63 | 2.8907 | 0.1429 |
| 3.1054 | 3.16 | 84 | 2.8089 | 0.1905 |
| 2.6316 | 4.16 | 105 | 2.7559 | 0.1905 |
| 2.9311 | 5.16 | 126 | 2.7195 | 0.1905 |
| 2.972 | 6.05 | 132 | 2.7184 | 0.1905 |
### Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0+cpu
- Datasets 2.1.0
- Tokenizers 0.13.3
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