metadata
base_model: microsoft/layoutlm-base-uncased
tags:
- generated_from_trainer
datasets:
- funsd
model-index:
- name: layoutlm-funsd
results: []
layoutlm-funsd
This model is a fine-tuned version of microsoft/layoutlm-base-uncased on the funsd dataset. It achieves the following results on the evaluation set:
- Loss: 1.0643
- Answer: {'precision': 0.384928716904277, 'recall': 0.4672435105067985, 'f1': 0.4221105527638191, 'number': 809}
- Header: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119}
- Question: {'precision': 0.5277088502894954, 'recall': 0.5990610328638498, 'f1': 0.5611257695690414, 'number': 1065}
- Overall Precision: 0.4583
- Overall Recall: 0.5098
- Overall F1: 0.4827
- Overall Accuracy: 0.6395
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: 3e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Answer | Header | Question | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|---|---|---|---|---|---|---|---|---|---|---|
| 1.4286 | 1.0 | 75 | 1.0643 | {'precision': 0.384928716904277, 'recall': 0.4672435105067985, 'f1': 0.4221105527638191, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.5277088502894954, 'recall': 0.5990610328638498, 'f1': 0.5611257695690414, 'number': 1065} | 0.4583 | 0.5098 | 0.4827 | 0.6395 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1