layoutmlv3_thursday_oct_7_v5

This model is a fine-tuned version of microsoft/layoutlmv3-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1171
  • Precision: 0.8763
  • Recall: 0.9075
  • F1: 0.8916
  • Accuracy: 0.9821

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 0.86 100 0.2961 0.8166 0.8559 0.8358 0.9372
No log 1.72 200 0.1481 0.8037 0.8594 0.8306 0.9674
No log 2.59 300 0.1191 0.8082 0.8772 0.8413 0.9753
No log 3.45 400 0.0892 0.8969 0.9128 0.9048 0.9844
0.29 4.31 500 0.1171 0.8763 0.9075 0.8916 0.9821
0.29 5.17 600 0.0994 0.8864 0.9021 0.8942 0.9818
0.29 6.03 700 0.0851 0.8901 0.8932 0.8917 0.9844
0.29 6.9 800 0.0957 0.8425 0.8950 0.8680 0.9814
0.29 7.76 900 0.0951 0.8735 0.8968 0.8850 0.9834
0.1351 8.62 1000 0.1005 0.8772 0.9021 0.8895 0.9840

Framework versions

  • Transformers 4.35.0.dev0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.14.1
Downloads last month
23
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for dwitidibyajyoti/layoutmlv3_thursday_oct_7_v5

Finetuned
(217)
this model