File size: 2,124 Bytes
d1e233c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 | ---
library_name: transformers
base_model: medicalai/ClinicalBERT
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: bert-section-classification-v5
results: []
---
<!-- 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. -->
# bert-section-classification-v5
This model is a fine-tuned version of [medicalai/ClinicalBERT](https://huggingface.co/medicalai/ClinicalBERT) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9710
- Accuracy: 0.8644
- Precision: 0.8671
- Recall: 0.8644
- F1: 0.8642
## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- num_epochs: 6
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log | 1.0 | 370 | 1.3245 | 0.2555 | 0.3090 | 0.2555 | 0.1199 |
| 1.3542 | 2.0 | 740 | 1.2024 | 0.7319 | 0.8115 | 0.7319 | 0.7163 |
| 1.2122 | 3.0 | 1110 | 1.1008 | 0.8675 | 0.8756 | 0.8675 | 0.8678 |
| 1.2122 | 4.0 | 1480 | 1.0275 | 0.8770 | 0.8834 | 0.8770 | 0.8773 |
| 1.082 | 5.0 | 1850 | 0.9855 | 0.8707 | 0.8751 | 0.8707 | 0.8706 |
| 1.003 | 6.0 | 2220 | 0.9710 | 0.8644 | 0.8671 | 0.8644 | 0.8642 |
### Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Tokenizers 0.21.1
|