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# videomae-base-groub23-24-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: 3.2558
- Accuracy: 0.1463

## 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: 80

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.8674        | 0.14  | 11   | 3.6587          | 0.0488   |
| 3.7787        | 1.14  | 22   | 3.5948          | 0.1220   |
| 3.6605        | 2.14  | 33   | 3.5183          | 0.1220   |
| 3.6081        | 3.14  | 44   | 3.4284          | 0.1463   |
| 3.5543        | 4.14  | 55   | 3.3461          | 0.1463   |
| 3.4024        | 5.14  | 66   | 3.2865          | 0.1220   |
| 3.3301        | 6.14  | 77   | 3.2581          | 0.1463   |
| 3.3935        | 7.04  | 80   | 3.2558          | 0.1463   |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.0+cpu
- Datasets 2.1.0
- Tokenizers 0.13.3

{"license": "cc-by-nc-4.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "MCG-NJU/videomae-base", "model-index": [{"name": "videomae-base-groub23-24-finetuned-SLT-subset", "results": []}]}
transformers pytorch videomae video-classification generated_from_trainer base_model:MCG-NJU/videomae-base license:cc-by-nc-4.0 endpoints_compatible region:us