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_headwise
  results: []
---

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# bert-base-uncased_1_16619_token_headwise

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: 0.2108
- Precision: 0.7761
- Recall: 0.8165
- F1: 0.7958
- Accuracy: 0.9460

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2219        | 1.0   | 1039  | 0.1919          | 0.7012    | 0.7769 | 0.7371 | 0.9361   |
| 0.1974        | 2.0   | 2078  | 0.1849          | 0.7284    | 0.7661 | 0.7468 | 0.9400   |
| 0.1868        | 3.0   | 3117  | 0.1791          | 0.7150    | 0.7880 | 0.7498 | 0.9407   |
| 0.1815        | 4.0   | 4156  | 0.1716          | 0.7576    | 0.7943 | 0.7756 | 0.9442   |
| 0.1766        | 5.0   | 5195  | 0.1727          | 0.7305    | 0.7843 | 0.7564 | 0.9425   |
| 0.1685        | 6.0   | 6234  | 0.1712          | 0.7378    | 0.7965 | 0.7660 | 0.9438   |
| 0.1672        | 7.0   | 7273  | 0.1742          | 0.7504    | 0.8255 | 0.7861 | 0.9443   |
| 0.1645        | 8.0   | 8312  | 0.1634          | 0.7545    | 0.8070 | 0.7798 | 0.9458   |
| 0.1629        | 9.0   | 9351  | 0.1672          | 0.7651    | 0.7970 | 0.7807 | 0.9456   |
| 0.1552        | 10.0  | 10390 | 0.1611          | 0.7567    | 0.8230 | 0.7885 | 0.9463   |
| 0.1548        | 11.0  | 11429 | 0.1689          | 0.7386    | 0.8026 | 0.7693 | 0.9439   |
| 0.1466        | 12.0  | 12468 | 0.1640          | 0.7539    | 0.8255 | 0.7881 | 0.9455   |
| 0.1509        | 13.0  | 13507 | 0.1639          | 0.7642    | 0.8172 | 0.7898 | 0.9466   |
| 0.1476        | 14.0  | 14546 | 0.1620          | 0.7580    | 0.8104 | 0.7833 | 0.9459   |
| 0.1461        | 15.0  | 15585 | 0.1604          | 0.7575    | 0.8214 | 0.7881 | 0.9458   |
| 0.1423        | 16.0  | 16624 | 0.1713          | 0.7540    | 0.8214 | 0.7862 | 0.9448   |
| 0.1413        | 17.0  | 17663 | 0.1626          | 0.7793    | 0.8075 | 0.7931 | 0.9470   |
| 0.1354        | 18.0  | 18702 | 0.1663          | 0.7599    | 0.8122 | 0.7852 | 0.9450   |
| 0.1316        | 19.0  | 19741 | 0.1720          | 0.7642    | 0.8019 | 0.7826 | 0.9439   |
| 0.1313        | 20.0  | 20780 | 0.1660          | 0.7812    | 0.8055 | 0.7932 | 0.9462   |
| 0.129         | 21.0  | 21819 | 0.1710          | 0.7667    | 0.8226 | 0.7937 | 0.9463   |
| 0.1267        | 22.0  | 22858 | 0.1671          | 0.7606    | 0.8278 | 0.7928 | 0.9455   |
| 0.1237        | 23.0  | 23897 | 0.1664          | 0.7567    | 0.8251 | 0.7895 | 0.9448   |
| 0.1205        | 24.0  | 24936 | 0.1701          | 0.7701    | 0.8145 | 0.7917 | 0.9457   |
| 0.1189        | 25.0  | 25975 | 0.1710          | 0.7652    | 0.8215 | 0.7924 | 0.9457   |
| 0.1194        | 26.0  | 27014 | 0.1677          | 0.7715    | 0.8302 | 0.7998 | 0.9469   |
| 0.1165        | 27.0  | 28053 | 0.1782          | 0.7731    | 0.8151 | 0.7935 | 0.9455   |
| 0.114         | 28.0  | 29092 | 0.1777          | 0.7618    | 0.8106 | 0.7854 | 0.9450   |
| 0.111         | 29.0  | 30131 | 0.1686          | 0.7681    | 0.8131 | 0.7900 | 0.9458   |
| 0.1081        | 30.0  | 31170 | 0.1707          | 0.7705    | 0.8217 | 0.7953 | 0.9471   |
| 0.1044        | 31.0  | 32209 | 0.1677          | 0.7777    | 0.8302 | 0.8031 | 0.9469   |
| 0.1042        | 32.0  | 33248 | 0.1785          | 0.7670    | 0.8215 | 0.7933 | 0.9467   |
| 0.1015        | 33.0  | 34287 | 0.1789          | 0.7685    | 0.8237 | 0.7951 | 0.9460   |
| 0.0996        | 34.0  | 35326 | 0.1771          | 0.7759    | 0.8205 | 0.7975 | 0.9459   |
| 0.0957        | 35.0  | 36365 | 0.1829          | 0.7741    | 0.8286 | 0.8004 | 0.9463   |
| 0.0938        | 36.0  | 37404 | 0.1834          | 0.7775    | 0.8244 | 0.8003 | 0.9461   |
| 0.0891        | 37.0  | 38443 | 0.1820          | 0.7682    | 0.8322 | 0.7989 | 0.9460   |
| 0.0874        | 38.0  | 39482 | 0.1905          | 0.7838    | 0.7999 | 0.7918 | 0.9448   |
| 0.087         | 39.0  | 40521 | 0.1915          | 0.7773    | 0.8165 | 0.7964 | 0.9460   |
| 0.0849        | 40.0  | 41560 | 0.1864          | 0.7734    | 0.8120 | 0.7922 | 0.9463   |
| 0.0819        | 41.0  | 42599 | 0.2028          | 0.7829    | 0.8093 | 0.7959 | 0.9464   |
| 0.0788        | 42.0  | 43638 | 0.1891          | 0.7689    | 0.8201 | 0.7937 | 0.9466   |
| 0.0776        | 43.0  | 44677 | 0.1941          | 0.7734    | 0.8259 | 0.7987 | 0.9469   |
| 0.0757        | 44.0  | 45716 | 0.2037          | 0.7794    | 0.8032 | 0.7911 | 0.9449   |
| 0.074         | 45.0  | 46755 | 0.2026          | 0.7660    | 0.8194 | 0.7918 | 0.9462   |
| 0.0722        | 46.0  | 47794 | 0.2089          | 0.7731    | 0.8147 | 0.7933 | 0.9460   |
| 0.0703        | 47.0  | 48833 | 0.2083          | 0.7772    | 0.8122 | 0.7943 | 0.9461   |
| 0.0687        | 48.0  | 49872 | 0.2077          | 0.7781    | 0.8179 | 0.7975 | 0.9464   |
| 0.0666        | 49.0  | 50911 | 0.2089          | 0.7747    | 0.8178 | 0.7956 | 0.9465   |
| 0.0669        | 50.0  | 51950 | 0.2108          | 0.7761    | 0.8165 | 0.7958 | 0.9460   |


### Framework versions

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