---
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: 0.5218963439132182
    - name: Recall
      type: recall
      value: 0.5781041388518025
    - name: F1
      type: f1
      value: 0.5485641891891893
    - name: Accuracy
      type: accuracy
      value: 0.8009761388286334
---

<!-- 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: 1.4328
- Precision: 0.5219
- Recall: 0.5781
- F1: 0.5486
- Accuracy: 0.8010

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 105  | 0.7200          | 0.4493    | 0.4833 | 0.4657 | 0.7785   |
| No log        | 2.0   | 210  | 0.7287          | 0.4381    | 0.5056 | 0.4694 | 0.7791   |
| No log        | 3.0   | 315  | 0.8443          | 0.4635    | 0.5207 | 0.4905 | 0.7823   |
| No log        | 4.0   | 420  | 1.0059          | 0.4780    | 0.5269 | 0.5013 | 0.7835   |
| 0.4225        | 5.0   | 525  | 0.9944          | 0.4688    | 0.5545 | 0.5081 | 0.7806   |
| 0.4225        | 6.0   | 630  | 1.0721          | 0.5104    | 0.5367 | 0.5232 | 0.7944   |
| 0.4225        | 7.0   | 735  | 1.1099          | 0.4829    | 0.5639 | 0.5202 | 0.7933   |
| 0.4225        | 8.0   | 840  | 1.2544          | 0.4814    | 0.5527 | 0.5146 | 0.7779   |
| 0.4225        | 9.0   | 945  | 1.2083          | 0.4823    | 0.5639 | 0.5199 | 0.7905   |
| 0.0481        | 10.0  | 1050 | 1.3132          | 0.4892    | 0.5621 | 0.5231 | 0.7924   |
| 0.0481        | 11.0  | 1155 | 1.3484          | 0.5040    | 0.5665 | 0.5334 | 0.7942   |
| 0.0481        | 12.0  | 1260 | 1.3297          | 0.5042    | 0.5585 | 0.5300 | 0.7989   |
| 0.0481        | 13.0  | 1365 | 1.3890          | 0.5023    | 0.5741 | 0.5358 | 0.7955   |
| 0.0481        | 14.0  | 1470 | 1.4140          | 0.5111    | 0.5639 | 0.5362 | 0.7985   |
| 0.009         | 15.0  | 1575 | 1.4130          | 0.5226    | 0.5550 | 0.5383 | 0.7996   |
| 0.009         | 16.0  | 1680 | 1.4197          | 0.5127    | 0.5639 | 0.5371 | 0.7964   |
| 0.009         | 17.0  | 1785 | 1.4166          | 0.5262    | 0.5723 | 0.5483 | 0.8015   |
| 0.009         | 18.0  | 1890 | 1.4257          | 0.5173    | 0.5781 | 0.5460 | 0.8004   |
| 0.009         | 19.0  | 1995 | 1.4318          | 0.5203    | 0.5817 | 0.5493 | 0.8011   |
| 0.0018        | 20.0  | 2100 | 1.4328          | 0.5219    | 0.5781 | 0.5486 | 0.8010   |


### Framework versions

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