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allways_pharma_v1.0
This model is a fine-tuned version of microsoft/layoutlmv3-base on the sroie dataset. It achieves the following results on the evaluation set:
- Loss: 0.5136
- Precision: 0.5
- Recall: 0.5
- F1: 0.5
- Accuracy: 0.8876
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: 800
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 25.0 | 100 | 0.1986 | 0.6364 | 0.6364 | 0.6364 | 0.9438 |
| No log | 50.0 | 200 | 0.3551 | 0.5909 | 0.5909 | 0.5909 | 0.9213 |
| No log | 75.0 | 300 | 0.5252 | 0.4583 | 0.5 | 0.4783 | 0.8876 |
| No log | 100.0 | 400 | 0.4834 | 0.5217 | 0.5455 | 0.5333 | 0.9101 |
| 0.0824 | 125.0 | 500 | 0.4642 | 0.5217 | 0.5455 | 0.5333 | 0.9101 |
| 0.0824 | 150.0 | 600 | 0.5076 | 0.5 | 0.5 | 0.5 | 0.8989 |
| 0.0824 | 175.0 | 700 | 0.5050 | 0.5 | 0.5 | 0.5 | 0.8876 |
| 0.0824 | 200.0 | 800 | 0.5136 | 0.5 | 0.5 | 0.5 | 0.8876 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.2.2
- Tokenizers 0.13.2
