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table-transformer-deep-dust-69
This model is a fine-tuned version of microsoft/table-transformer-detection on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7515
- Loss Ce: 0.0037
- Loss Bbox: 0.1065
- Cardinality Error: 1.0018
- Giou: 89.1969
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: 4
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Loss Ce | Loss Bbox | Cardinality Error | Giou |
|---|---|---|---|---|---|---|---|
| 1.0999 | 0.2 | 500 | 1.1217 | 0.1327 | 0.1393 | 1.0018 | 85.2782 |
| 0.7151 | 0.4 | 1000 | 0.9541 | 0.0420 | 0.1291 | 1.0018 | 86.5834 |
| 0.5844 | 0.6 | 1500 | 0.8440 | 0.0255 | 0.1161 | 1.0018 | 88.1012 |
| 0.5046 | 0.8 | 2000 | 0.7986 | 0.0177 | 0.1109 | 1.0018 | 88.6059 |
| 0.4826 | 1.0 | 2500 | 0.7727 | 0.0132 | 0.1078 | 1.0018 | 88.9256 |
| 0.3942 | 1.2 | 3000 | 0.8233 | 0.0097 | 0.1159 | 1.0018 | 88.2610 |
| 0.4361 | 1.4 | 3500 | 0.7496 | 0.0080 | 0.1054 | 1.0018 | 89.2268 |
| 0.3225 | 1.6 | 4000 | 0.7584 | 0.0066 | 0.1067 | 1.0018 | 89.0580 |
| 0.371 | 1.8 | 4500 | 0.7559 | 0.0060 | 0.1068 | 1.0018 | 89.1710 |
| 0.3759 | 2.0 | 5000 | 0.7732 | 0.0051 | 0.1094 | 1.0018 | 88.8865 |
| 0.3031 | 2.2 | 5500 | 0.7353 | 0.0049 | 0.1040 | 1.0018 | 89.4293 |
| 0.3806 | 2.4 | 6000 | 0.7551 | 0.0042 | 0.1068 | 1.0018 | 89.1146 |
| 0.2889 | 2.6 | 6500 | 0.7529 | 0.0039 | 0.1066 | 1.0018 | 89.1589 |
| 0.2847 | 2.8 | 7000 | 0.7487 | 0.0038 | 0.1060 | 1.0018 | 89.2153 |
| 0.2906 | 3.0 | 7500 | 0.7515 | 0.0037 | 0.1065 | 1.0018 | 89.1969 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
