---
license: cc0-1.0
base_model: bionlp/bluebert_pubmed_uncased_L-12_H-768_A-12
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: NHS-bluebert-multi
  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. -->

# NHS-bluebert-multi

This model is a fine-tuned version of [bionlp/bluebert_pubmed_uncased_L-12_H-768_A-12](https://huggingface.co/bionlp/bluebert_pubmed_uncased_L-12_H-768_A-12) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8729
- Accuracy: 0.7098
- Precision: 0.7153
- Recall: 0.7098
- F1: 0.7118

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.1093        | 1.0   | 397  | 0.7138          | 0.7243   | 0.7288    | 0.7243 | 0.7262 |
| 0.0518        | 2.0   | 794  | 0.8117          | 0.7073   | 0.7007    | 0.7073 | 0.6926 |
| 1.9889        | 3.0   | 1191 | 0.8729          | 0.7098   | 0.7153    | 0.7098 | 0.7118 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2