---
language:
- en
license: mit
base_model: distilbert-base-uncased
tags:
- low-resource NER
- token_classification
- biomedicine
- medical NER
- generated_from_trainer
datasets:
- medicine
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: Dagobert42/distilbert-base-uncased-biored-finetuned
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Dagobert42/distilbert-base-uncased-biored-finetuned

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the bigbio/biored dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6976
- Accuracy: 0.7703
- Precision: 0.5335
- Recall: 0.424
- F1: 0.4652
- Weighted F1: 0.7512

## 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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Weighted F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-----------:|
| No log        | 1.0   | 25   | 0.9181          | 0.7144   | 0.4183    | 0.1593 | 0.151  | 0.6108      |
| No log        | 2.0   | 50   | 0.8580          | 0.7283   | 0.5273    | 0.2252 | 0.2508 | 0.6404      |
| No log        | 3.0   | 75   | 0.8232          | 0.7369   | 0.5603    | 0.2769 | 0.3173 | 0.6638      |
| No log        | 4.0   | 100  | 0.7814          | 0.7476   | 0.5184    | 0.3618 | 0.4085 | 0.7031      |
| No log        | 5.0   | 125  | 0.7691          | 0.7507   | 0.5306    | 0.3929 | 0.4283 | 0.7173      |
| No log        | 6.0   | 150  | 0.7492          | 0.7607   | 0.5494    | 0.3919 | 0.4396 | 0.7244      |
| No log        | 7.0   | 175  | 0.7616          | 0.7622   | 0.5553    | 0.4048 | 0.4481 | 0.728       |
| No log        | 8.0   | 200  | 0.7256          | 0.7657   | 0.5437    | 0.4306 | 0.4717 | 0.7426      |
| No log        | 9.0   | 225  | 0.7413          | 0.7684   | 0.5565    | 0.4315 | 0.4739 | 0.7422      |
| No log        | 10.0  | 250  | 0.7497          | 0.7721   | 0.5606    | 0.4364 | 0.4789 | 0.7446      |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.15.0