<!-- 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. -->
Translado
This model is a fine-tuned version of microsoft/layoutlmv3-large on the sroie dataset. It achieves the following results on the evaluation set:
- Loss: 0.0307
- Precision: 0.9484
- Recall: 0.9951
- F1: 0.9712
- Accuracy: 0.9977
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: 2
- eval_batch_size: 2
- 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 | 4.17 | 100 | 0.0244 | 0.9484 | 0.9951 | 0.9712 | 0.9977 |
| No log | 8.33 | 200 | 0.0265 | 0.9484 | 0.9951 | 0.9712 | 0.9977 |
| No log | 12.5 | 300 | 0.0277 | 0.9484 | 0.9951 | 0.9712 | 0.9977 |
| No log | 16.67 | 400 | 0.0286 | 0.9484 | 0.9951 | 0.9712 | 0.9977 |
| 0.0134 | 20.83 | 500 | 0.0293 | 0.9484 | 0.9951 | 0.9712 | 0.9977 |
| 0.0134 | 25.0 | 600 | 0.0298 | 0.9484 | 0.9951 | 0.9712 | 0.9977 |
| 0.0134 | 29.17 | 700 | 0.0302 | 0.9484 | 0.9951 | 0.9712 | 0.9977 |
| 0.0134 | 33.33 | 800 | 0.0305 | 0.9484 | 0.9951 | 0.9712 | 0.9977 |
| 0.0134 | 37.5 | 900 | 0.0306 | 0.9484 | 0.9951 | 0.9712 | 0.9977 |
| 0.0 | 41.67 | 1000 | 0.0307 | 0.9484 | 0.9951 | 0.9712 | 0.9977 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.2.2
- Tokenizers 0.13.2
