---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- crows_pairs
metrics:
- accuracy
model-index:
- name: bert-base-uncased_crows_pairs_finetuned
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: crows_pairs
      type: crows_pairs
      config: crows_pairs
      split: test
      args: crows_pairs
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7649006622516556
---

<!-- 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-base-uncased_crows_pairs_finetuned

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the crows_pairs dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1731
- Accuracy: 0.7649
- Tp: 0.3344
- Tn: 0.4305
- Fp: 0.1126
- Fn: 0.1225

## 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: 0.0001
- 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 | Accuracy | Tp     | Tn     | Fp     | Fn     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|
| 0.703         | 1.05  | 20   | 0.6889          | 0.5430   | 0.0    | 0.5430 | 0.0    | 0.4570 |
| 0.6884        | 2.11  | 40   | 0.6886          | 0.5      | 0.3013 | 0.1987 | 0.3444 | 0.1556 |
| 0.5388        | 3.16  | 60   | 0.6347          | 0.7053   | 0.1821 | 0.5232 | 0.0199 | 0.2748 |
| 0.2228        | 4.21  | 80   | 0.9802          | 0.6987   | 0.1887 | 0.5099 | 0.0331 | 0.2682 |
| 0.1644        | 5.26  | 100  | 0.7523          | 0.7583   | 0.3675 | 0.3907 | 0.1523 | 0.0894 |
| 0.0478        | 6.32  | 120  | 1.5712          | 0.6954   | 0.2053 | 0.4901 | 0.0530 | 0.2517 |
| 0.0465        | 7.37  | 140  | 1.2587          | 0.7351   | 0.2781 | 0.4570 | 0.0861 | 0.1788 |
| 0.0313        | 8.42  | 160  | 1.5825          | 0.7450   | 0.3775 | 0.3675 | 0.1755 | 0.0795 |
| 0.0137        | 9.47  | 180  | 1.3570          | 0.7318   | 0.2815 | 0.4503 | 0.0927 | 0.1755 |
| 0.04          | 10.53 | 200  | 2.1377          | 0.6921   | 0.1887 | 0.5033 | 0.0397 | 0.2682 |
| 0.0041        | 11.58 | 220  | 1.6776          | 0.7351   | 0.3278 | 0.4073 | 0.1358 | 0.1291 |
| 0.0042        | 12.63 | 240  | 1.8873          | 0.7086   | 0.2980 | 0.4106 | 0.1325 | 0.1589 |
| 0.0009        | 13.68 | 260  | 2.2464          | 0.6987   | 0.3543 | 0.3444 | 0.1987 | 0.1026 |
| 0.014         | 14.74 | 280  | 1.9753          | 0.7252   | 0.3245 | 0.4007 | 0.1424 | 0.1325 |
| 0.0026        | 15.79 | 300  | 1.8852          | 0.7417   | 0.2914 | 0.4503 | 0.0927 | 0.1656 |
| 0.0147        | 16.84 | 320  | 2.0273          | 0.7351   | 0.3113 | 0.4238 | 0.1192 | 0.1457 |
| 0.0009        | 17.89 | 340  | 1.7328          | 0.7483   | 0.3278 | 0.4205 | 0.1225 | 0.1291 |
| 0.0085        | 18.95 | 360  | 2.0146          | 0.7450   | 0.2815 | 0.4636 | 0.0795 | 0.1755 |
| 0.0001        | 20.0  | 380  | 2.0808          | 0.7450   | 0.3113 | 0.4338 | 0.1093 | 0.1457 |
| 0.0001        | 21.05 | 400  | 2.2655          | 0.7417   | 0.3609 | 0.3808 | 0.1623 | 0.0960 |
| 0.0034        | 22.11 | 420  | 2.0298          | 0.7583   | 0.3079 | 0.4503 | 0.0927 | 0.1490 |
| 0.0082        | 23.16 | 440  | 2.0650          | 0.7550   | 0.3344 | 0.4205 | 0.1225 | 0.1225 |
| 0.0001        | 24.21 | 460  | 2.2472          | 0.7450   | 0.2748 | 0.4702 | 0.0728 | 0.1821 |
| 0.0001        | 25.26 | 480  | 2.3655          | 0.7351   | 0.3709 | 0.3642 | 0.1788 | 0.0861 |
| 0.0004        | 26.32 | 500  | 2.1407          | 0.7550   | 0.3510 | 0.4040 | 0.1391 | 0.1060 |
| 0.0001        | 27.37 | 520  | 2.1168          | 0.7450   | 0.3642 | 0.3808 | 0.1623 | 0.0927 |
| 0.0002        | 28.42 | 540  | 2.2050          | 0.7517   | 0.3775 | 0.3742 | 0.1689 | 0.0795 |
| 0.0           | 29.47 | 560  | 2.0560          | 0.7682   | 0.3212 | 0.4470 | 0.0960 | 0.1358 |
| 0.0           | 30.53 | 580  | 2.0859          | 0.7715   | 0.3179 | 0.4536 | 0.0894 | 0.1391 |
| 0.0           | 31.58 | 600  | 2.0958          | 0.7715   | 0.3179 | 0.4536 | 0.0894 | 0.1391 |
| 0.0           | 32.63 | 620  | 2.1039          | 0.7715   | 0.3179 | 0.4536 | 0.0894 | 0.1391 |
| 0.0           | 33.68 | 640  | 2.1113          | 0.7715   | 0.3179 | 0.4536 | 0.0894 | 0.1391 |
| 0.0           | 34.74 | 660  | 2.1180          | 0.7715   | 0.3179 | 0.4536 | 0.0894 | 0.1391 |
| 0.0           | 35.79 | 680  | 2.1127          | 0.7715   | 0.3278 | 0.4437 | 0.0993 | 0.1291 |
| 0.0           | 36.84 | 700  | 2.1376          | 0.7682   | 0.3377 | 0.4305 | 0.1126 | 0.1192 |
| 0.0           | 37.89 | 720  | 2.1460          | 0.7616   | 0.3377 | 0.4238 | 0.1192 | 0.1192 |
| 0.0           | 38.95 | 740  | 2.1507          | 0.7649   | 0.3377 | 0.4272 | 0.1159 | 0.1192 |
| 0.0           | 40.0  | 760  | 2.1548          | 0.7682   | 0.3377 | 0.4305 | 0.1126 | 0.1192 |
| 0.0           | 41.05 | 780  | 2.1586          | 0.7682   | 0.3377 | 0.4305 | 0.1126 | 0.1192 |
| 0.0           | 42.11 | 800  | 2.1620          | 0.7682   | 0.3377 | 0.4305 | 0.1126 | 0.1192 |
| 0.0           | 43.16 | 820  | 2.1649          | 0.7682   | 0.3377 | 0.4305 | 0.1126 | 0.1192 |
| 0.0           | 44.21 | 840  | 2.1674          | 0.7682   | 0.3377 | 0.4305 | 0.1126 | 0.1192 |
| 0.0           | 45.26 | 860  | 2.1690          | 0.7682   | 0.3377 | 0.4305 | 0.1126 | 0.1192 |
| 0.0           | 46.32 | 880  | 2.1705          | 0.7682   | 0.3377 | 0.4305 | 0.1126 | 0.1192 |
| 0.0           | 47.37 | 900  | 2.1717          | 0.7649   | 0.3344 | 0.4305 | 0.1126 | 0.1225 |
| 0.0           | 48.42 | 920  | 2.1726          | 0.7649   | 0.3344 | 0.4305 | 0.1126 | 0.1225 |
| 0.0           | 49.47 | 940  | 2.1731          | 0.7649   | 0.3344 | 0.4305 | 0.1126 | 0.1225 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2