paper_model_2 / README.md
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End of training
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metadata
base_model: microsoft/dit-base-finetuned-rvlcdip
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: paper_model_2
    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: 1

paper_model_2

This model is a fine-tuned version of microsoft/dit-base-finetuned-rvlcdip on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0013
  • Accuracy: 1.0

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
0.0167 0.9954 162 0.0135 0.9966
0.0032 1.9969 325 0.0030 0.9992
0.0038 2.9985 488 0.0021 0.9992
0.0022 4.0 651 0.0013 1.0
0.0016 4.9770 810 0.0013 1.0

Framework versions

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