readme: ---
  license: cc-by-nc-sa-4.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: layoutlmv2-er-ner
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # layoutlmv2-er-ner
  
  This model is a fine-tuned version of [renjithks/layoutlmv2-cord-ner](https://huggingface.co/renjithks/layoutlmv2-cord-ner) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1217
  - Precision: 0.7810
  - Recall: 0.8085
  - F1: 0.7945
  - Accuracy: 0.9747
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 41   | 0.5441          | 0.0       | 0.0    | 0.0    | 0.8851   |
  | No log        | 2.0   | 82   | 0.4660          | 0.1019    | 0.0732 | 0.0852 | 0.8690   |
  | No log        | 3.0   | 123  | 0.2506          | 0.4404    | 0.4828 | 0.4606 | 0.9240   |
  | No log        | 4.0   | 164  | 0.1725          | 0.6120    | 0.6076 | 0.6098 | 0.9529   |
  | No log        | 5.0   | 205  | 0.1387          | 0.7204    | 0.7245 | 0.7225 | 0.9671   |
  | No log        | 6.0   | 246  | 0.1237          | 0.7742    | 0.7747 | 0.7745 | 0.9722   |
  | No log        | 7.0   | 287  | 0.1231          | 0.7619    | 0.7554 | 0.7586 | 0.9697   |
  | No log        | 8.0   | 328  | 0.1199          | 0.7994    | 0.7719 | 0.7854 | 0.9738   |
  | No log        | 9.0   | 369  | 0.1197          | 0.7937    | 0.8113 | 0.8024 | 0.9741   |
  | No log        | 10.0  | 410  | 0.1284          | 0.7581    | 0.7597 | 0.7589 | 0.9690   |
  | No log        | 11.0  | 451  | 0.1172          | 0.7792    | 0.7848 | 0.7820 | 0.9738   |
  | No log        | 12.0  | 492  | 0.1192          | 0.7913    | 0.7970 | 0.7941 | 0.9743   |
  | 0.1858        | 13.0  | 533  | 0.1175          | 0.7960    | 0.8006 | 0.7983 | 0.9753   |
  | 0.1858        | 14.0  | 574  | 0.1184          | 0.7724    | 0.8034 | 0.7876 | 0.9740   |
  | 0.1858        | 15.0  | 615  | 0.1171          | 0.7882    | 0.8142 | 0.8010 | 0.9756   |
  | 0.1858        | 16.0  | 656  | 0.1195          | 0.7829    | 0.8070 | 0.7948 | 0.9745   |
  | 0.1858        | 17.0  | 697  | 0.1209          | 0.7810    | 0.8006 | 0.7906 | 0.9743   |
  | 0.1858        | 18.0  | 738  | 0.1241          | 0.7806    | 0.7963 | 0.7884 | 0.9740   |
  | 0.1858        | 19.0  | 779  | 0.1222          | 0.7755    | 0.8027 | 0.7889 | 0.9742   |
  | 0.1858        | 20.0  | 820  | 0.1217          | 0.7810    | 0.8085 | 0.7945 | 0.9747   |
  
  
  ### Framework versions
  
  - Transformers 4.16.2
  - Pytorch 1.9.0+cu111
  - Datasets 1.18.4
  - Tokenizers 0.11.6
  