---
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: emea
      split: validation
      args: emea
    metrics:
    - name: Precision
      type: precision
      value: 0.7103274559193955
    - name: Recall
      type: recall
      value: 0.7359081419624217
    - name: F1
      type: f1
      value: 0.7228915662650602
    - name: Accuracy
      type: accuracy
      value: 0.9223586595037094
---

<!-- 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: 0.3775
- Precision: 0.7103
- Recall: 0.7359
- F1: 0.7229
- Accuracy: 0.9224

## 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: 2e-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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 61   | 0.3947          | 0.7117    | 0.6905 | 0.7009 | 0.9198   |
| No log        | 2.0   | 122  | 0.3738          | 0.7210    | 0.7244 | 0.7227 | 0.9224   |
| No log        | 3.0   | 183  | 0.3775          | 0.7103    | 0.7359 | 0.7229 | 0.9224   |


### Framework versions

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