<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
layoutlmv3-finetuned-cord_500
This model is a fine-tuned version of microsoft/layoutlmv3-base on the cord-layoutlmv3 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2339
- Precision: 0.9509
- Recall: 0.9573
- F1: 0.9541
- Accuracy: 0.9610
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: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 4000
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 2.5 | 250 | 0.9950 | 0.7114 | 0.7784 | 0.7434 | 0.7903 |
| 1.3831 | 5.0 | 500 | 0.5152 | 0.8483 | 0.8787 | 0.8632 | 0.8816 |
| 1.3831 | 7.5 | 750 | 0.3683 | 0.9013 | 0.9154 | 0.9083 | 0.9240 |
| 0.3551 | 10.0 | 1000 | 0.3051 | 0.9201 | 0.9304 | 0.9252 | 0.9363 |
| 0.3551 | 12.5 | 1250 | 0.2636 | 0.9375 | 0.9424 | 0.9399 | 0.9457 |
| 0.1562 | 15.0 | 1500 | 0.2498 | 0.9385 | 0.9476 | 0.9430 | 0.9508 |
| 0.1562 | 17.5 | 1750 | 0.2380 | 0.9414 | 0.9499 | 0.9456 | 0.9559 |
| 0.0863 | 20.0 | 2000 | 0.2355 | 0.9400 | 0.9491 | 0.9445 | 0.9542 |
| 0.0863 | 22.5 | 2250 | 0.2268 | 0.9451 | 0.9536 | 0.9493 | 0.9601 |
| 0.0512 | 25.0 | 2500 | 0.2277 | 0.9429 | 0.9513 | 0.9471 | 0.9588 |
| 0.0512 | 27.5 | 2750 | 0.2315 | 0.9473 | 0.9551 | 0.9512 | 0.9593 |
| 0.0358 | 30.0 | 3000 | 0.2294 | 0.9509 | 0.9573 | 0.9541 | 0.9605 |
| 0.0358 | 32.5 | 3250 | 0.2330 | 0.9458 | 0.9543 | 0.9501 | 0.9593 |
| 0.028 | 35.0 | 3500 | 0.2374 | 0.9487 | 0.9558 | 0.9523 | 0.9597 |
| 0.028 | 37.5 | 3750 | 0.2374 | 0.9501 | 0.9558 | 0.9530 | 0.9593 |
| 0.0244 | 40.0 | 4000 | 0.2339 | 0.9509 | 0.9573 | 0.9541 | 0.9610 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
