distilbert-base-uncased-ICU-Readmission-classification_test1.1_ClinicalBERT
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3311
- F1: 0.5192
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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.6328 | 1.0 | 125 | 0.6717 | 0.7654 |
| 0.7109 | 2.0 | 250 | 0.6969 | 0.5385 |
| 0.5117 | 3.0 | 375 | 0.7038 | 0.6179 |
| 0.5039 | 4.0 | 500 | 0.7655 | 0.5487 |
| 0.457 | 5.0 | 625 | 0.8232 | 0.6667 |
| 0.625 | 6.0 | 750 | 0.9869 | 0.5472 |
| 0.8516 | 7.0 | 875 | 1.2391 | 0.5234 |
| 0.2031 | 8.0 | 1000 | 1.2022 | 0.5094 |
| 0.0559 | 9.0 | 1125 | 1.2742 | 0.5143 |
| 0.0505 | 10.0 | 1250 | 1.3311 | 0.5192 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for NgechuJohn/distilbert-base-uncased-ICU-Readmission-classification_test1.1_ClinicalBERT
Base model
distilbert/distilbert-base-uncased