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

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

This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on the bigbio/biored dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1566
- Accuracy: 0.9536
- Precision: 0.8629
- Recall: 0.8326
- F1: 0.8434
- Weighted F1: 0.9537

## 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: 1.5e-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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Weighted F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-----------:|
| No log        | 1.0   | 20   | 0.2106          | 0.9319   | 0.8365    | 0.7555 | 0.7918 | 0.9299      |
| No log        | 2.0   | 40   | 0.2015          | 0.9358   | 0.8014    | 0.8012 | 0.7993 | 0.9352      |
| No log        | 3.0   | 60   | 0.1974          | 0.9409   | 0.8459    | 0.81   | 0.8264 | 0.9401      |
| No log        | 4.0   | 80   | 0.1952          | 0.9433   | 0.8383    | 0.8176 | 0.8272 | 0.9425      |
| No log        | 5.0   | 100  | 0.2013          | 0.9438   | 0.8469    | 0.8162 | 0.8294 | 0.9434      |
| No log        | 6.0   | 120  | 0.2012          | 0.9435   | 0.8362    | 0.8135 | 0.8237 | 0.9432      |
| No log        | 7.0   | 140  | 0.2048          | 0.9459   | 0.8293    | 0.8071 | 0.8173 | 0.945       |
| No log        | 8.0   | 160  | 0.2070          | 0.9454   | 0.8142    | 0.8132 | 0.8126 | 0.9449      |
| No log        | 9.0   | 180  | 0.2163          | 0.9456   | 0.8528    | 0.8063 | 0.8279 | 0.9447      |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.1+cu117
- Datasets 2.18.0
- Tokenizers 0.15.0