---
license: mit
base_model: microsoft/layoutlm-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: layoutlm-funsd-tf
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# layoutlm-funsd-tf

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:
- Train Loss: 0.0961
- Validation Loss: 1.5766
- Train Overall Precision: 0.5302
- Train Overall Recall: 0.6121
- Train Overall F1: 0.5682
- Train Overall Accuracy: 0.6392
- Epoch: 31

## 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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: mixed_float16

### Training results

| Train Loss | Validation Loss | Train Overall Precision | Train Overall Recall | Train Overall F1 | Train Overall Accuracy | Epoch |
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
| 1.7401     | 1.5464          | 0.0930                  | 0.1174               | 0.1038           | 0.3843                 | 0     |
| 1.4833     | 1.3301          | 0.2414                  | 0.3964               | 0.3000           | 0.4268                 | 1     |
| 1.2693     | 1.2622          | 0.2985                  | 0.4947               | 0.3724           | 0.4693                 | 2     |
| 1.1369     | 1.0729          | 0.3617                  | 0.4887               | 0.4157           | 0.5902                 | 3     |
| 1.0364     | 1.1800          | 0.3293                  | 0.5073               | 0.3994           | 0.5604                 | 4     |
| 0.9327     | 1.2033          | 0.3938                  | 0.5268               | 0.4507           | 0.5683                 | 5     |
| 0.8211     | 1.0876          | 0.4192                  | 0.5153               | 0.4623           | 0.6004                 | 6     |
| 0.7265     | 1.0982          | 0.4480                  | 0.5334               | 0.4869           | 0.6102                 | 7     |
| 0.6561     | 1.1134          | 0.4490                  | 0.5650               | 0.5003           | 0.6192                 | 8     |
| 0.5783     | 1.0834          | 0.4764                  | 0.5630               | 0.5161           | 0.6317                 | 9     |
| 0.5160     | 1.1453          | 0.4504                  | 0.5494               | 0.4950           | 0.6227                 | 10    |
| 0.4714     | 1.1865          | 0.4873                  | 0.5981               | 0.5371           | 0.6277                 | 11    |
| 0.4340     | 1.2212          | 0.4972                  | 0.5805               | 0.5356           | 0.6318                 | 12    |
| 0.3990     | 1.2407          | 0.4913                  | 0.6212               | 0.5486           | 0.6334                 | 13    |
| 0.3743     | 1.2597          | 0.5173                  | 0.5986               | 0.5550           | 0.6338                 | 14    |
| 0.3454     | 1.2205          | 0.5157                  | 0.6106               | 0.5592           | 0.6406                 | 15    |
| 0.3276     | 1.3600          | 0.5186                  | 0.6001               | 0.5564           | 0.6318                 | 16    |
| 0.3013     | 1.6473          | 0.4805                  | 0.5745               | 0.5233           | 0.5899                 | 17    |
| 0.3093     | 1.2595          | 0.4957                  | 0.5735               | 0.5318           | 0.6389                 | 18    |
| 0.2577     | 1.4449          | 0.4772                  | 0.5675               | 0.5185           | 0.6076                 | 19    |
| 0.2301     | 1.4514          | 0.4790                  | 0.5620               | 0.5172           | 0.6205                 | 20    |
| 0.2118     | 1.4575          | 0.5255                  | 0.5991               | 0.5599           | 0.6305                 | 21    |
| 0.1845     | 1.4446          | 0.5270                  | 0.6076               | 0.5644           | 0.6353                 | 22    |
| 0.1698     | 1.4538          | 0.5428                  | 0.6011               | 0.5705           | 0.6423                 | 23    |
| 0.1606     | 1.4318          | 0.5131                  | 0.5720               | 0.5409           | 0.6361                 | 24    |
| 0.1538     | 1.4257          | 0.5310                  | 0.6061               | 0.5661           | 0.6484                 | 25    |
| 0.1403     | 1.5233          | 0.5232                  | 0.6061               | 0.5616           | 0.6428                 | 26    |
| 0.1229     | 1.4796          | 0.5547                  | 0.6131               | 0.5825           | 0.6471                 | 27    |
| 0.1225     | 1.5841          | 0.5239                  | 0.5946               | 0.5570           | 0.6101                 | 28    |
| 0.1085     | 1.5432          | 0.5253                  | 0.6046               | 0.5622           | 0.6423                 | 29    |
| 0.1025     | 1.5414          | 0.5176                  | 0.5966               | 0.5543           | 0.6312                 | 30    |
| 0.0961     | 1.5766          | 0.5302                  | 0.6121               | 0.5682           | 0.6392                 | 31    |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.15.0
- Datasets 2.17.0
- Tokenizers 0.15.2