|
--- |
|
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: 0.2511 |
|
- Validation Loss: 0.6882 |
|
- Train Overall Precision: 0.7189 |
|
- Train Overall Recall: 0.7878 |
|
- Train Overall F1: 0.7517 |
|
- Train Overall Accuracy: 0.8039 |
|
- 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 | |
|
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:| |
|
| 1.6546 | 1.3264 | 0.3384 | 0.3708 | 0.3538 | 0.5774 | 0 | |
|
| 1.0901 | 0.8303 | 0.6013 | 0.6508 | 0.6251 | 0.7392 | 1 | |
|
| 0.7169 | 0.6666 | 0.6778 | 0.7441 | 0.7094 | 0.7864 | 2 | |
|
| 0.5285 | 0.6429 | 0.6859 | 0.7702 | 0.7256 | 0.8022 | 3 | |
|
| 0.4270 | 0.6216 | 0.7089 | 0.7832 | 0.7442 | 0.8092 | 4 | |
|
| 0.3451 | 0.6699 | 0.7038 | 0.7832 | 0.7414 | 0.7972 | 5 | |
|
| 0.2867 | 0.6886 | 0.7203 | 0.7868 | 0.7520 | 0.7965 | 6 | |
|
| 0.2511 | 0.6882 | 0.7189 | 0.7878 | 0.7517 | 0.8039 | 7 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.0 |
|
- TensorFlow 2.15.0 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.19.1 |
|
|
