Edit model card

layoutlmv2-finetuned-piimask

This model is a fine-tuned version of microsoft/layoutlmv2-large-uncased on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1939
  • Precision: 0.7555
  • Recall: 0.7775
  • F1: 0.7663
  • Accuracy: 0.9581

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: 2
  • eval_batch_size: 8
  • seed: 42
  • 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
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 135 0.1473 0.7251 0.6697 0.6963 0.9499
No log 2.0 270 0.1400 0.6767 0.7573 0.7147 0.9621
No log 3.0 405 0.1543 0.7372 0.7753 0.7558 0.9612
0.3116 4.0 540 0.2355 0.7621 0.7775 0.7697 0.9560
0.3116 5.0 675 0.1939 0.7555 0.7775 0.7663 0.9581

Framework versions

  • Transformers 4.42.3
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
Downloads last month
7
Safetensors
Model size
426M params
Tensor type
F32
·
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 vaibhav1411/layoutlmv2-finetuned-piimask

Finetuned
(3)
this model