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---
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
should probably proofread and complete it, then remove this comment. -->
# 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: 0.1527
- Accuracy: 0.9501
- Precision: 0.8539
- Recall: 0.8292
- F1: 0.8405
- Weighted F1: 0.95
## 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 | 20 | 0.2071 | 0.9301 | 0.8427 | 0.744 | 0.7851 | 0.9282 |
| No log | 2.0 | 40 | 0.1945 | 0.9378 | 0.8251 | 0.8091 | 0.8159 | 0.9368 |
| No log | 3.0 | 60 | 0.1952 | 0.9403 | 0.8461 | 0.8125 | 0.828 | 0.9397 |
| No log | 4.0 | 80 | 0.1981 | 0.942 | 0.8486 | 0.8211 | 0.8339 | 0.9414 |
| No log | 5.0 | 100 | 0.2051 | 0.9436 | 0.8376 | 0.8228 | 0.8296 | 0.943 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1+cu117
- Datasets 2.18.0
- Tokenizers 0.15.0
|