metadata
base_model: layoutlmv3
tags:
- generated_from_trainer
datasets:
- mp-02/cord
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-finetuned-cord
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: mp-02/cord
type: mp-02/cord
metrics:
- name: Precision
type: precision
value: 0.9220389805097451
- name: Recall
type: recall
value: 0.9549689440993789
- name: F1
type: f1
value: 0.9382151029748284
- name: Accuracy
type: accuracy
value: 0.934634974533107
layoutlmv3-finetuned-cord
This model is a fine-tuned version of layoutlmv3 on the mp-02/cord dataset. It achieves the following results on the evaluation set:
- Loss: 0.3103
- Precision: 0.9220
- Recall: 0.9550
- F1: 0.9382
- Accuracy: 0.9346
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: 1e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 3.7313 | 250 | 0.7079 | 0.8180 | 0.8657 | 0.8412 | 0.8476 |
| 1.064 | 7.4627 | 500 | 0.4029 | 0.8791 | 0.9255 | 0.9017 | 0.9138 |
| 1.064 | 11.1940 | 750 | 0.3349 | 0.9132 | 0.9480 | 0.9303 | 0.9308 |
| 0.294 | 14.9254 | 1000 | 0.3103 | 0.9220 | 0.9550 | 0.9382 | 0.9346 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1