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ClinicalBERT-finetuned-ner-pablo-just-classifier
pabRomero/ClinicalBERT-finetuned-ner-pablo-just-classifier
ClinicalBERT-finetuned-ner-pablo-just-classifier is a machine learning model from pabRomero. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Model type
- distilbert
- Access
- Public
- Created
- Aug 17, 2024
- Updated
- Aug 17, 2024
- SHA
- e04beaaf
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
ClinicalBERT-finetuned-ner-pablo-just-classifier
This model is a fine-tuned version of medicalai/ClinicalBERT on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1567
- Precision: 0.7118
- Recall: 0.7328
- F1: 0.7221
- Accuracy: 0.9650
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: 0.1
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.495 | 0.9996 | 652 | 0.3446 | 0.6425 | 0.6934 | 0.6670 | 0.9575 |
| 0.3703 | 1.9992 | 1304 | 0.1567 | 0.7118 | 0.7328 | 0.7221 | 0.9650 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0+cu124
- Datasets 2.21.0
- Tokenizers 0.19.1
- Type
- distilbert
- Created
- Aug 17, 2024
- Updated
- Aug 17, 2024