ser-model-microsoft / README.md
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metadata
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: ser-model-microsoft
    results: []

ser-model-microsoft

This model is a fine-tuned version of microsoft/layoutlmv3-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2762
  • Precision: 0.6
  • Recall: 0.9
  • F1: 0.7200
  • Accuracy: 0.925

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: 1e-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • training_steps: 100

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 5.0 10 0.9255 0.0 0.0 0.0 0.7
No log 10.0 20 0.6668 0.4444 0.4 0.4211 0.7875
No log 15.0 30 0.4304 0.6667 0.8 0.7273 0.85
No log 20.0 40 0.4050 0.6667 0.8 0.7273 0.85
No log 25.0 50 0.5639 0.8 0.8 0.8000 0.8125
No log 30.0 60 0.2429 0.8 0.8 0.8000 0.925
No log 35.0 70 0.4434 0.6667 0.8 0.7273 0.8625
No log 40.0 80 0.2817 0.6 0.9 0.7200 0.925
No log 45.0 90 0.2784 0.6 0.9 0.7200 0.925
No log 50.0 100 0.2762 0.6 0.9 0.7200 0.925

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.1