camembert-base-finetuned-ICDCode_5
This model is a fine-tuned version of camembert-base on the None dataset. It has been trained on a corpus of death certificate. One ICDCode is given for a given cause of death or commorbidities. As it is an important task to be able to predict these ICDCode, I shave trained this model for 8 epochs on 400 000 death causes. Pre-processing of noisy data points was mandatory before tokenization. It allows us to get this accuracy. It achieves the following results on the evaluation set:
- Loss: 0.6574
- Accuracy: 0.8964
- F1: 0.8750
- Recall: 0.8964
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: 2e-05
- train_batch_size: 50
- eval_batch_size: 50
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall |
---|---|---|---|---|---|---|
3.7466 | 1.0 | 4411 | 1.9448 | 0.7201 | 0.6541 | 0.7201 |
1.5264 | 2.0 | 8822 | 1.2045 | 0.8134 | 0.7691 | 0.8134 |
1.0481 | 3.0 | 13233 | 0.9473 | 0.8513 | 0.8149 | 0.8513 |
0.8304 | 4.0 | 17644 | 0.8098 | 0.8718 | 0.8427 | 0.8718 |
0.7067 | 5.0 | 22055 | 0.7352 | 0.8834 | 0.8574 | 0.8834 |
0.6285 | 6.0 | 26466 | 0.6911 | 0.8898 | 0.8659 | 0.8898 |
0.5779 | 7.0 | 30877 | 0.6641 | 0.8958 | 0.8741 | 0.8958 |
0.549 | 8.0 | 35288 | 0.6574 | 0.8964 | 0.8750 | 0.8964 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
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