---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-medical-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. -->

# bert-medical-ner

This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1905
- Precision: 0.6552
- Recall: 0.6965
- F1: 0.6752
- Accuracy: 0.7449

## 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: 64
- eval_batch_size: 64
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 71   | 1.8255          | 0.3427    | 0.4460 | 0.3876 | 0.5555   |
| No log        | 2.0   | 142  | 1.3139          | 0.4722    | 0.5703 | 0.5166 | 0.6442   |
| No log        | 3.0   | 213  | 1.1147          | 0.5258    | 0.6029 | 0.5617 | 0.6886   |
| No log        | 4.0   | 284  | 0.9873          | 0.5785    | 0.6151 | 0.5962 | 0.7048   |
| No log        | 5.0   | 355  | 0.9282          | 0.6314    | 0.6558 | 0.6434 | 0.7312   |
| No log        | 6.0   | 426  | 0.8760          | 0.642     | 0.6538 | 0.6478 | 0.7329   |
| No log        | 7.0   | 497  | 0.8501          | 0.6608    | 0.6904 | 0.6753 | 0.7466   |
| 1.1706        | 8.0   | 568  | 0.8313          | 0.6791    | 0.7067 | 0.6926 | 0.7483   |
| 1.1706        | 9.0   | 639  | 0.8002          | 0.6616    | 0.7047 | 0.6824 | 0.7449   |
| 1.1706        | 10.0  | 710  | 0.8280          | 0.6640    | 0.6721 | 0.6680 | 0.7363   |
| 1.1706        | 11.0  | 781  | 0.8248          | 0.6594    | 0.6823 | 0.6707 | 0.7457   |
| 1.1706        | 12.0  | 852  | 0.7988          | 0.6610    | 0.7189 | 0.6888 | 0.7654   |
| 1.1706        | 13.0  | 923  | 0.8593          | 0.6587    | 0.6762 | 0.6673 | 0.7423   |
| 1.1706        | 14.0  | 994  | 0.8204          | 0.6719    | 0.6965 | 0.6840 | 0.7534   |
| 0.4317        | 15.0  | 1065 | 0.8478          | 0.6770    | 0.7128 | 0.6944 | 0.7526   |
| 0.4317        | 16.0  | 1136 | 0.8855          | 0.6610    | 0.7149 | 0.6869 | 0.7730   |
| 0.4317        | 17.0  | 1207 | 0.9091          | 0.6751    | 0.7067 | 0.6905 | 0.7560   |
| 0.4317        | 18.0  | 1278 | 0.9201          | 0.6555    | 0.7169 | 0.6848 | 0.7568   |
| 0.4317        | 19.0  | 1349 | 0.9840          | 0.6623    | 0.7189 | 0.6895 | 0.7483   |
| 0.4317        | 20.0  | 1420 | 0.9817          | 0.6833    | 0.7251 | 0.7036 | 0.7543   |
| 0.4317        | 21.0  | 1491 | 0.9958          | 0.6583    | 0.6945 | 0.6759 | 0.7509   |
| 0.2121        | 22.0  | 1562 | 0.9340          | 0.6647    | 0.7026 | 0.6832 | 0.7722   |
| 0.2121        | 23.0  | 1633 | 0.9906          | 0.6622    | 0.7108 | 0.6857 | 0.7619   |
| 0.2121        | 24.0  | 1704 | 1.0099          | 0.6692    | 0.7088 | 0.6884 | 0.7526   |
| 0.2121        | 25.0  | 1775 | 1.0627          | 0.6673    | 0.7189 | 0.6922 | 0.7662   |
| 0.2121        | 26.0  | 1846 | 1.0744          | 0.6584    | 0.7067 | 0.6817 | 0.7637   |
| 0.2121        | 27.0  | 1917 | 1.1328          | 0.6569    | 0.6864 | 0.6713 | 0.7389   |
| 0.2121        | 28.0  | 1988 | 1.0799          | 0.6641    | 0.7128 | 0.6876 | 0.7577   |
| 0.1201        | 29.0  | 2059 | 1.1156          | 0.6628    | 0.7047 | 0.6831 | 0.7568   |
| 0.1201        | 30.0  | 2130 | 1.0839          | 0.6628    | 0.6965 | 0.6792 | 0.75     |
| 0.1201        | 31.0  | 2201 | 1.1511          | 0.6526    | 0.6925 | 0.6719 | 0.7389   |
| 0.1201        | 32.0  | 2272 | 1.1140          | 0.6737    | 0.7149 | 0.6937 | 0.7543   |
| 0.1201        | 33.0  | 2343 | 1.1094          | 0.6609    | 0.6986 | 0.6792 | 0.7466   |
| 0.1201        | 34.0  | 2414 | 1.1332          | 0.6755    | 0.7251 | 0.6994 | 0.7534   |
| 0.1201        | 35.0  | 2485 | 1.1322          | 0.6841    | 0.7189 | 0.7011 | 0.7551   |
| 0.0776        | 36.0  | 2556 | 1.1603          | 0.6711    | 0.7189 | 0.6942 | 0.7551   |
| 0.0776        | 37.0  | 2627 | 1.1460          | 0.6504    | 0.7047 | 0.6764 | 0.7543   |
| 0.0776        | 38.0  | 2698 | 1.1387          | 0.6584    | 0.7067 | 0.6817 | 0.7577   |
| 0.0776        | 39.0  | 2769 | 1.1438          | 0.6641    | 0.7088 | 0.6857 | 0.7534   |
| 0.0776        | 40.0  | 2840 | 1.1791          | 0.6660    | 0.7149 | 0.6896 | 0.7577   |
| 0.0776        | 41.0  | 2911 | 1.1701          | 0.6641    | 0.7088 | 0.6857 | 0.75     |
| 0.0776        | 42.0  | 2982 | 1.1889          | 0.6615    | 0.6965 | 0.6786 | 0.7457   |
| 0.0571        | 43.0  | 3053 | 1.1810          | 0.6533    | 0.6945 | 0.6732 | 0.7449   |
| 0.0571        | 44.0  | 3124 | 1.1944          | 0.6577    | 0.6965 | 0.6766 | 0.7440   |
| 0.0571        | 45.0  | 3195 | 1.2032          | 0.6564    | 0.6925 | 0.6739 | 0.7432   |
| 0.0571        | 46.0  | 3266 | 1.2092          | 0.6609    | 0.6945 | 0.6773 | 0.7449   |
| 0.0571        | 47.0  | 3337 | 1.1864          | 0.6622    | 0.6986 | 0.6799 | 0.7466   |
| 0.0571        | 48.0  | 3408 | 1.1972          | 0.6538    | 0.6925 | 0.6726 | 0.7449   |
| 0.0571        | 49.0  | 3479 | 1.1899          | 0.6545    | 0.6945 | 0.6739 | 0.7449   |
| 0.0467        | 50.0  | 3550 | 1.1905          | 0.6552    | 0.6965 | 0.6752 | 0.7449   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3