---
license: apache-2.0
base_model: Dr-BERT/DrBERT-7GB
tags:
- generated_from_trainer
datasets:
- quaero
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: drbert-7gb-finedtuned-ner
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: quaero
      type: quaero
      config: medline
      split: validation
      args: medline
    metrics:
    - name: Precision
      type: precision
      value: 0.5105965463108321
    - name: Recall
      type: recall
      value: 0.5789942145082332
    - name: F1
      type: f1
      value: 0.5426485922836287
    - name: Accuracy
      type: accuracy
      value: 0.8011795010845987
---

<!-- 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. -->

# drbert-7gb-finedtuned-ner

This model is a fine-tuned version of [Dr-BERT/DrBERT-7GB](https://huggingface.co/Dr-BERT/DrBERT-7GB) on the quaero dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2226
- Precision: 0.5106
- Recall: 0.5790
- F1: 0.5426
- Accuracy: 0.8012

## 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: 5e-05
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 105  | 0.7160          | 0.4596    | 0.4713 | 0.4654 | 0.7764   |
| No log        | 2.0   | 210  | 0.6985          | 0.4484    | 0.5220 | 0.4824 | 0.7831   |
| No log        | 3.0   | 315  | 0.8448          | 0.4872    | 0.5234 | 0.5046 | 0.7881   |
| No log        | 4.0   | 420  | 0.9029          | 0.5231    | 0.5403 | 0.5315 | 0.8017   |
| 0.4116        | 5.0   | 525  | 1.0169          | 0.4813    | 0.5656 | 0.5200 | 0.7892   |
| 0.4116        | 6.0   | 630  | 1.0596          | 0.5150    | 0.5665 | 0.5395 | 0.7986   |
| 0.4116        | 7.0   | 735  | 1.1298          | 0.4954    | 0.5705 | 0.5303 | 0.8000   |
| 0.4116        | 8.0   | 840  | 1.1665          | 0.4949    | 0.5803 | 0.5342 | 0.7984   |
| 0.4116        | 9.0   | 945  | 1.2045          | 0.5135    | 0.5754 | 0.5427 | 0.8025   |
| 0.0254        | 10.0  | 1050 | 1.2226          | 0.5106    | 0.5790 | 0.5426 | 0.8012   |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2