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paper_model_DP_1

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paper_model_DP_1
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---
license: apache-2.0
base_model: jordyvl/resnet50_rvl-cdip
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: paper_model_DP_1
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: test
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9924496644295302
---

<!-- 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. -->

# paper_model_DP_1

This model is a fine-tuned version of [jordyvl/resnet50_rvl-cdip](https://huggingface.co/jordyvl/resnet50_rvl-cdip) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0283
- Accuracy: 0.9924

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.1263        | 0.9954 | 162  | 0.0981          | 0.9622   |
| 0.0733        | 1.9969 | 325  | 0.0436          | 0.9891   |
| 0.0491        | 2.9985 | 488  | 0.0276          | 0.9874   |
| 0.0286        | 4.0    | 651  | 0.0266          | 0.9908   |
| 0.0321        | 4.9770 | 810  | 0.0283          | 0.9924   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1