---
library_name: transformers
license: apache-2.0
base_model: michiyasunaga/BioLinkBERT-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
model-index:
- name: BioLinkBERT-mimic-phi-ner
  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. -->

# BioLinkBERT-mimic-phi-ner

This model is a fine-tuned version of [michiyasunaga/BioLinkBERT-base](https://huggingface.co/michiyasunaga/BioLinkBERT-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0153
- F1 Macro: 0.9100
- F1 Weighted: 0.9100
- Precision: 0.8749
- Recall: 0.9481
- F1 Name: 0.92
- F1 Location: 0.88
- F1 Phone: 0.91
- F1 Date: 0.9
- F1 Mrn: 0.65
- F1 Account: 0.66
- F1 Age Over 89: 0.0
- F1 Device Id: 0.5
- F1 Ssn: 0.39
- F1 Url: 0.15
- F1 Email: 0.12

## 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: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | F1 Macro | F1 Weighted | Precision | Recall | F1 Name | F1 Location | F1 Phone | F1 Date | F1 Mrn | F1 Account | F1 Age Over 89 | F1 Device Id | F1 Ssn | F1 Url | F1 Email |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-----------:|:---------:|:------:|:-------:|:-----------:|:--------:|:-------:|:------:|:----------:|:--------------:|:------------:|:------:|:------:|:--------:|
| 0.8832        | 0.2020 | 300  | 0.2738          | 0.5399   | 0.5399      | 0.4427    | 0.6917 | 0.64    | 0.31        | 0.22     | 0.16    | 0.05   | 0.79       | 0.14           | 0.0          | 0.0    | 0.0    | 0.0      |
| 0.2048        | 0.4039 | 600  | 0.0948          | 0.7961   | 0.7961      | 0.7392    | 0.8624 | 0.85    | 0.58        | 0.7      | 0.64    | 0.47   | 0.9        | 0.0            | 0.0          | 0.0    | 0.0    | 0.0      |
| 0.1982        | 0.6059 | 900  | 0.0432          | 0.7818   | 0.7818      | 0.7165    | 0.8602 | 0.83    | 0.61        | 0.82     | 0.66    | 0.35   | 0.6        | 0.0            | 0.0          | 0.0    | 0.0    | 0.0      |
| 0.0654        | 0.8078 | 1200 | 0.0325          | 0.8718   | 0.8718      | 0.8240    | 0.9255 | 0.9     | 0.79        | 0.85     | 0.85    | 0.46   | 0.75       | 0.0            | 0.19         | 0.19   | 0.12   | 0.0      |
| 0.0755        | 1.0094 | 1500 | 0.0219          | 0.8969   | 0.8969      | 0.8590    | 0.9383 | 0.92    | 0.86        | 0.89     | 0.88    | 0.67   | 0.67       | 0.0            | 0.23         | 0.15   | 0.0    | 0.0      |
| 0.0614        | 1.2114 | 1800 | 0.0174          | 0.8885   | 0.8885      | 0.8412    | 0.9415 | 0.91    | 0.87        | 0.88     | 0.83    | 0.48   | 0.66       | 0.0            | 0.15         | 0.18   | 0.0    | 0.0      |
| 0.0241        | 1.4133 | 2100 | 0.0165          | 0.9065   | 0.9065      | 0.8701    | 0.9460 | 0.92    | 0.88        | 0.91     | 0.9     | 0.66   | 0.66       | 0.0            | 0.35         | 0.29   | 0.0    | 0.0      |
| 0.0414        | 1.6153 | 2400 | 0.0175          | 0.9193   | 0.9193      | 0.8895    | 0.9512 | 0.93    | 0.89        | 0.91     | 0.89    | 0.65   | 0.66       | 0.0            | 0.33         | 0.36   | 0.15   | 0.12     |
| 0.0303        | 1.8172 | 2700 | 0.0153          | 0.9100   | 0.9100      | 0.8749    | 0.9481 | 0.92    | 0.88        | 0.91     | 0.9     | 0.65   | 0.66       | 0.0            | 0.5          | 0.39   | 0.15   | 0.12     |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2