Downloads · 30 days
5
19% of all-time downloads
ClinicalBERT-finetuned-ner-pablo-classifier-then-full-model
pabRomero/ClinicalBERT-finetuned-ner-pablo-classifier-then-full-model
ClinicalBERT-finetuned-ner-pablo-classifier-then-full-model 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. --
All-time downloads
26
Public
Parameters
135M
2.2 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors539 MB · 99%
At a glance
- Model type
- distilbert
- Access
- Public
- Created
- Aug 17, 2024
- Updated
- Aug 17, 2024
- SHA
- efd6e46b
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-classifier-then-full-model
This model is a fine-tuned version of pabRomero/ClinicalBERT-finetuned-ner-pablo-just-classifier on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1259
- Precision: 0.8091
- Recall: 0.8039
- F1: 0.8065
- Accuracy: 0.9716
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: 0.0002
- 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: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1613 | 0.9996 | 652 | 0.1321 | 0.8184 | 0.7378 | 0.7760 | 0.9674 |
| 0.1048 | 1.9992 | 1304 | 0.1060 | 0.7999 | 0.7652 | 0.7822 | 0.9708 |
| 0.0745 | 2.9989 | 1956 | 0.1124 | 0.8016 | 0.7960 | 0.7988 | 0.9708 |
| 0.0349 | 3.9985 | 2608 | 0.1259 | 0.8091 | 0.8039 | 0.8065 | 0.9716 |
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