|
--- |
|
license: mit |
|
tags: |
|
- generated_from_keras_callback |
|
base_model: microsoft/layoutlm-base-uncased |
|
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: 0.5937 |
|
- Validation Loss: 1.1902 |
|
- Train Overall Precision: 0.4751 |
|
- Train Overall Recall: 0.5850 |
|
- Train Overall F1: 0.5244 |
|
- Train Overall Accuracy: 0.6201 |
|
- Epoch: 7 |
|
|
|
## 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': 3e-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 | |
|
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:| |
|
| 1.6536 | 1.4851 | 0.1737 | 0.3176 | 0.2245 | 0.4025 | 0 | |
|
| 1.3258 | 1.2951 | 0.2957 | 0.4325 | 0.3513 | 0.4737 | 1 | |
|
| 1.1768 | 1.1266 | 0.3614 | 0.4892 | 0.4157 | 0.5489 | 2 | |
|
| 1.0113 | 1.0274 | 0.3889 | 0.5294 | 0.4484 | 0.6040 | 3 | |
|
| 0.9157 | 1.0104 | 0.4428 | 0.5414 | 0.4871 | 0.6152 | 4 | |
|
| 0.7484 | 1.0807 | 0.4742 | 0.5354 | 0.5029 | 0.6153 | 5 | |
|
| 0.6791 | 1.2077 | 0.4709 | 0.5434 | 0.5045 | 0.6049 | 6 | |
|
| 0.5937 | 1.1902 | 0.4751 | 0.5850 | 0.5244 | 0.6201 | 7 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.1 |
|
- TensorFlow 2.15.0 |
|
- Datasets 2.17.1 |
|
- Tokenizers 0.15.2 |
|
|
