---
license: mit
base_model: microsoft/BiomedNLP-KRISSBERT-PubMed-UMLS-EL
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
- f1
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [microsoft/BiomedNLP-KRISSBERT-PubMed-UMLS-EL](https://huggingface.co/microsoft/BiomedNLP-KRISSBERT-PubMed-UMLS-EL) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4228
- Precision: 0.9215
- Recall: 0.9209
- Accuracy: 0.9211
- F1: 0.9210

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:------:|
| No log        | 1.0   | 308  | 0.3266          | 0.8847    | 0.8822 | 0.8820   | 0.8824 |
| 0.4217        | 2.0   | 616  | 0.3034          | 0.9072    | 0.9066 | 0.9064   | 0.9065 |
| 0.4217        | 3.0   | 924  | 0.3483          | 0.9171    | 0.9170 | 0.9170   | 0.9171 |
| 0.163         | 4.0   | 1232 | 0.3952          | 0.9227    | 0.9227 | 0.9227   | 0.9226 |
| 0.0722        | 5.0   | 1540 | 0.4228          | 0.9215    | 0.9209 | 0.9211   | 0.9210 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2