---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv1-cord-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. -->

# layoutlmv1-cord-ner

This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1438
- Precision: 0.9336
- Recall: 0.9453
- F1: 0.9394
- Accuracy: 0.9767

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 113  | 0.1251          | 0.9054    | 0.9184 | 0.9119 | 0.9651   |
| No log        | 2.0   | 226  | 0.1343          | 0.9002    | 0.9261 | 0.9130 | 0.9635   |
| No log        | 3.0   | 339  | 0.1264          | 0.9189    | 0.9357 | 0.9272 | 0.9647   |
| No log        | 4.0   | 452  | 0.1235          | 0.9122    | 0.9376 | 0.9248 | 0.9681   |
| 0.1371        | 5.0   | 565  | 0.1353          | 0.9378    | 0.9405 | 0.9391 | 0.9717   |
| 0.1371        | 6.0   | 678  | 0.1431          | 0.9233    | 0.9357 | 0.9295 | 0.9709   |
| 0.1371        | 7.0   | 791  | 0.1473          | 0.9289    | 0.9405 | 0.9347 | 0.9759   |
| 0.1371        | 8.0   | 904  | 0.1407          | 0.9473    | 0.9491 | 0.9482 | 0.9784   |
| 0.0106        | 9.0   | 1017 | 0.1440          | 0.9301    | 0.9453 | 0.9376 | 0.9769   |
| 0.0106        | 10.0  | 1130 | 0.1438          | 0.9336    | 0.9453 | 0.9394 | 0.9767   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1