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# dit-base-finetuned-rvlcdip-finetuned-document-classifier

This model is a fine-tuned version of [microsoft/dit-base-finetuned-rvlcdip](https://huggingface.co/microsoft/dit-base-finetuned-rvlcdip) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4756
- Accuracy: 0.936

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.5664        | 0.9577 | 17   | 1.3503          | 0.624    |
| 1.1861        | 1.9577 | 34   | 0.9458          | 0.888    |
| 0.7973        | 2.9577 | 51   | 0.6490          | 0.92     |
| 0.7129        | 3.9577 | 68   | 0.5158          | 0.928    |
| 0.5476        | 4.9577 | 85   | 0.4756          | 0.936    |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1

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