prajwalJumde's picture
am-infoweb/MRR-NER-08-09-Layoutlmv3
a1292c7
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: MRR-NER-08-09-Layoutlmv3
    results: []

MRR-NER-08-09-Layoutlmv3

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: 0.0175
  • Precision: 0.8367
  • Recall: 0.9111
  • F1: 0.8723
  • Accuracy: 0.9960

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: 1000

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 8.33 100 0.2585 0.1667 0.0222 0.0392 0.9607
No log 16.67 200 0.1281 0.4783 0.2444 0.3235 0.9727
No log 25.0 300 0.0821 0.3696 0.3778 0.3736 0.9767
No log 33.33 400 0.0493 0.5111 0.5111 0.5111 0.9813
0.2244 41.67 500 0.0330 0.625 0.7778 0.6931 0.9913
0.2244 50.0 600 0.0272 0.6909 0.8444 0.7600 0.9927
0.2244 58.33 700 0.0218 0.7843 0.8889 0.8333 0.9953
0.2244 66.67 800 0.0190 0.7547 0.8889 0.8163 0.9947
0.2244 75.0 900 0.0158 0.8936 0.9333 0.9130 0.9973
0.038 83.33 1000 0.0175 0.8367 0.9111 0.8723 0.9960

Framework versions

  • Transformers 4.34.0.dev0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3