|
--- |
|
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: 0.2445 |
|
- Validation Loss: 0.6550 |
|
- Train Overall Precision: 0.7272 |
|
- Train Overall Recall: 0.7893 |
|
- Train Overall F1: 0.7570 |
|
- Train Overall Accuracy: 0.8195 |
|
- 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 | |
|
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:| |
|
| 1.6675 | 1.3532 | 0.3327 | 0.3477 | 0.3400 | 0.5549 | 0 | |
|
| 1.0883 | 0.8340 | 0.6022 | 0.6713 | 0.6349 | 0.7466 | 1 | |
|
| 0.7296 | 0.6953 | 0.6452 | 0.7501 | 0.6937 | 0.7836 | 2 | |
|
| 0.5398 | 0.6647 | 0.6832 | 0.7672 | 0.7228 | 0.7895 | 3 | |
|
| 0.4379 | 0.6258 | 0.7092 | 0.7697 | 0.7382 | 0.8069 | 4 | |
|
| 0.3622 | 0.6494 | 0.7240 | 0.8003 | 0.7602 | 0.8095 | 5 | |
|
| 0.3033 | 0.6519 | 0.7096 | 0.7983 | 0.7514 | 0.8111 | 6 | |
|
| 0.2445 | 0.6550 | 0.7272 | 0.7893 | 0.7570 | 0.8195 | 7 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.26.1 |
|
- TensorFlow 2.11.0 |
|
- Datasets 2.9.0 |
|
- Tokenizers 0.13.2 |
|
|
