pytorch generated_from_trainer dataset:bionlp2004 license:apache-2.0 region:us
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- bionlp2004
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-uncased_1_16619_token
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-base-uncased_1_16619_token

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the bionlp2004 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1660
- Precision: 0.7730
- Recall: 0.8185
- F1: 0.7951
- Accuracy: 0.9478

## 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: 0.001
- 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: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.233         | 1.0   | 1039  | 0.1956          | 0.6860    | 0.7301 | 0.7073 | 0.9331   |
| 0.2099        | 2.0   | 2078  | 0.1890          | 0.7214    | 0.7508 | 0.7358 | 0.9370   |
| 0.1991        | 3.0   | 3117  | 0.1862          | 0.7058    | 0.7785 | 0.7404 | 0.9375   |
| 0.19          | 4.0   | 4156  | 0.1736          | 0.7420    | 0.7943 | 0.7673 | 0.9434   |
| 0.1894        | 5.0   | 5195  | 0.1748          | 0.7319    | 0.7722 | 0.7515 | 0.9417   |
| 0.1814        | 6.0   | 6234  | 0.1686          | 0.7351    | 0.7952 | 0.7640 | 0.9427   |
| 0.177         | 7.0   | 7273  | 0.1682          | 0.7404    | 0.8086 | 0.7730 | 0.9448   |
| 0.1756        | 8.0   | 8312  | 0.1740          | 0.7386    | 0.7796 | 0.7585 | 0.9423   |
| 0.1761        | 9.0   | 9351  | 0.1691          | 0.7442    | 0.7664 | 0.7551 | 0.9430   |
| 0.1693        | 10.0  | 10390 | 0.1641          | 0.7506    | 0.8113 | 0.7797 | 0.9446   |
| 0.1697        | 11.0  | 11429 | 0.1669          | 0.7297    | 0.7938 | 0.7604 | 0.9427   |
| 0.1607        | 12.0  | 12468 | 0.1654          | 0.7593    | 0.8185 | 0.7878 | 0.9454   |
| 0.1643        | 13.0  | 13507 | 0.1652          | 0.7288    | 0.8035 | 0.7644 | 0.9430   |
| 0.1618        | 14.0  | 14546 | 0.1592          | 0.7548    | 0.7988 | 0.7762 | 0.9464   |
| 0.1598        | 15.0  | 15585 | 0.1641          | 0.7575    | 0.8006 | 0.7785 | 0.9454   |
| 0.16          | 16.0  | 16624 | 0.1621          | 0.7440    | 0.8174 | 0.7790 | 0.9456   |
| 0.1572        | 17.0  | 17663 | 0.1669          | 0.7598    | 0.8015 | 0.7801 | 0.9453   |
| 0.1528        | 18.0  | 18702 | 0.1680          | 0.7332    | 0.8073 | 0.7685 | 0.9427   |
| 0.1513        | 19.0  | 19741 | 0.1653          | 0.7630    | 0.7920 | 0.7772 | 0.9453   |
| 0.1504        | 20.0  | 20780 | 0.1635          | 0.7645    | 0.8073 | 0.7853 | 0.9461   |
| 0.1491        | 21.0  | 21819 | 0.1591          | 0.7547    | 0.8262 | 0.7889 | 0.9473   |
| 0.1455        | 22.0  | 22858 | 0.1627          | 0.7634    | 0.8145 | 0.7881 | 0.9457   |
| 0.145         | 23.0  | 23897 | 0.1584          | 0.7529    | 0.8210 | 0.7855 | 0.9464   |
| 0.1438        | 24.0  | 24936 | 0.1603          | 0.7592    | 0.8012 | 0.7796 | 0.9466   |
| 0.1413        | 25.0  | 25975 | 0.1614          | 0.7699    | 0.8134 | 0.7911 | 0.9470   |
| 0.1437        | 26.0  | 27014 | 0.1594          | 0.7557    | 0.8226 | 0.7877 | 0.9465   |
| 0.1414        | 27.0  | 28053 | 0.1605          | 0.7680    | 0.8183 | 0.7923 | 0.9478   |
| 0.1385        | 28.0  | 29092 | 0.1631          | 0.7588    | 0.8028 | 0.7802 | 0.9459   |
| 0.1365        | 29.0  | 30131 | 0.1568          | 0.7701    | 0.8167 | 0.7927 | 0.9482   |
| 0.1352        | 30.0  | 31170 | 0.1607          | 0.7660    | 0.8271 | 0.7954 | 0.9481   |
| 0.1331        | 31.0  | 32209 | 0.1646          | 0.7627    | 0.8122 | 0.7867 | 0.9461   |
| 0.1328        | 32.0  | 33248 | 0.1658          | 0.7560    | 0.8176 | 0.7856 | 0.9464   |
| 0.1319        | 33.0  | 34287 | 0.1579          | 0.7639    | 0.8228 | 0.7923 | 0.9486   |
| 0.1309        | 34.0  | 35326 | 0.1595          | 0.7666    | 0.8151 | 0.7901 | 0.9471   |
| 0.1271        | 35.0  | 36365 | 0.1616          | 0.7645    | 0.8248 | 0.7935 | 0.9476   |
| 0.1262        | 36.0  | 37404 | 0.1615          | 0.7641    | 0.8104 | 0.7866 | 0.9464   |
| 0.1227        | 37.0  | 38443 | 0.1614          | 0.7667    | 0.8273 | 0.7958 | 0.9475   |
| 0.1207        | 38.0  | 39482 | 0.1640          | 0.7763    | 0.8014 | 0.7887 | 0.9472   |
| 0.1212        | 39.0  | 40521 | 0.1613          | 0.7716    | 0.8142 | 0.7923 | 0.9487   |
| 0.1192        | 40.0  | 41560 | 0.1596          | 0.7773    | 0.8196 | 0.7979 | 0.9493   |
| 0.1193        | 41.0  | 42599 | 0.1684          | 0.7769    | 0.8071 | 0.7917 | 0.9473   |
| 0.1171        | 42.0  | 43638 | 0.1636          | 0.7717    | 0.8183 | 0.7943 | 0.9471   |
| 0.1146        | 43.0  | 44677 | 0.1613          | 0.7675    | 0.8217 | 0.7937 | 0.9476   |
| 0.1154        | 44.0  | 45716 | 0.1648          | 0.7725    | 0.8066 | 0.7892 | 0.9467   |
| 0.1149        | 45.0  | 46755 | 0.1660          | 0.7745    | 0.8172 | 0.7953 | 0.9476   |
| 0.1133        | 46.0  | 47794 | 0.1655          | 0.7742    | 0.8187 | 0.7958 | 0.9480   |
| 0.1121        | 47.0  | 48833 | 0.1659          | 0.7768    | 0.8156 | 0.7957 | 0.9481   |
| 0.1104        | 48.0  | 49872 | 0.1663          | 0.7714    | 0.8129 | 0.7916 | 0.9478   |
| 0.1069        | 49.0  | 50911 | 0.1659          | 0.7746    | 0.8163 | 0.7949 | 0.9479   |
| 0.11          | 50.0  | 51950 | 0.1660          | 0.7730    | 0.8185 | 0.7951 | 0.9478   |


### Framework versions

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