transformers pytorch bert text-classification generated_from_trainer dataset:crows_pairs license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- crows_pairs
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: multiberts-seed_0_crows_pairs_classifieronly
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: crows_pairs
      type: crows_pairs
      config: crows_pairs
      split: test
      args: crows_pairs
    metrics:
    - type: accuracy
      value: 0.5132450331125827
      name: Accuracy
---

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# multiberts-seed_0_crows_pairs_classifieronly

This model is a fine-tuned version of [google/multiberts-seed_0](https://huggingface.co/google/multiberts-seed_0) on the crows_pairs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6940
- Accuracy: 0.5132
- Tp: 0.0695
- Tn: 0.4437
- Fp: 0.0199
- Fn: 0.4669

## 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: 5e-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 | Accuracy | Tp     | Tn     | Fp     | Fn     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|
| 0.7145        | 1.05  | 20   | 0.6927          | 0.5166   | 0.4172 | 0.0993 | 0.3642 | 0.1192 |
| 0.7091        | 2.11  | 40   | 0.6916          | 0.5166   | 0.4967 | 0.0199 | 0.4437 | 0.0397 |
| 0.7005        | 3.16  | 60   | 0.6943          | 0.4702   | 0.1854 | 0.2848 | 0.1788 | 0.3510 |
| 0.7106        | 4.21  | 80   | 0.6976          | 0.4669   | 0.0033 | 0.4636 | 0.0    | 0.5331 |
| 0.7038        | 5.26  | 100  | 0.6933          | 0.5132   | 0.3411 | 0.1722 | 0.2914 | 0.1954 |
| 0.7012        | 6.32  | 120  | 0.6974          | 0.4669   | 0.0033 | 0.4636 | 0.0    | 0.5331 |
| 0.7           | 7.37  | 140  | 0.6918          | 0.5199   | 0.4768 | 0.0430 | 0.4205 | 0.0596 |
| 0.7082        | 8.42  | 160  | 0.6960          | 0.4702   | 0.0066 | 0.4636 | 0.0    | 0.5298 |
| 0.699         | 9.47  | 180  | 0.6936          | 0.5199   | 0.2781 | 0.2417 | 0.2219 | 0.2583 |
| 0.7004        | 10.53 | 200  | 0.7043          | 0.4636   | 0.0    | 0.4636 | 0.0    | 0.5364 |
| 0.6948        | 11.58 | 220  | 0.6907          | 0.5232   | 0.5199 | 0.0033 | 0.4603 | 0.0166 |
| 0.7132        | 12.63 | 240  | 0.6979          | 0.4669   | 0.0033 | 0.4636 | 0.0    | 0.5331 |
| 0.7062        | 13.68 | 260  | 0.6930          | 0.5232   | 0.3444 | 0.1788 | 0.2848 | 0.1921 |
| 0.6983        | 14.74 | 280  | 0.6966          | 0.4669   | 0.0033 | 0.4636 | 0.0    | 0.5331 |
| 0.6996        | 15.79 | 300  | 0.6927          | 0.5265   | 0.3742 | 0.1523 | 0.3113 | 0.1623 |
| 0.7039        | 16.84 | 320  | 0.6972          | 0.4669   | 0.0033 | 0.4636 | 0.0    | 0.5331 |
| 0.6862        | 17.89 | 340  | 0.6914          | 0.5232   | 0.4967 | 0.0265 | 0.4371 | 0.0397 |
| 0.6943        | 18.95 | 360  | 0.6947          | 0.4934   | 0.0430 | 0.4503 | 0.0132 | 0.4934 |
| 0.7063        | 20.0  | 380  | 0.6907          | 0.5232   | 0.5199 | 0.0033 | 0.4603 | 0.0166 |
| 0.7087        | 21.05 | 400  | 0.6947          | 0.4834   | 0.0331 | 0.4503 | 0.0132 | 0.5033 |
| 0.7033        | 22.11 | 420  | 0.6945          | 0.4934   | 0.0464 | 0.4470 | 0.0166 | 0.4901 |
| 0.7025        | 23.16 | 440  | 0.6934          | 0.4967   | 0.2185 | 0.2781 | 0.1854 | 0.3179 |
| 0.7035        | 24.21 | 460  | 0.6944          | 0.5033   | 0.0563 | 0.4470 | 0.0166 | 0.4801 |
| 0.6958        | 25.26 | 480  | 0.6941          | 0.5199   | 0.0795 | 0.4404 | 0.0232 | 0.4570 |
| 0.6955        | 26.32 | 500  | 0.6946          | 0.4868   | 0.0364 | 0.4503 | 0.0132 | 0.5    |
| 0.7046        | 27.37 | 520  | 0.6932          | 0.5199   | 0.2715 | 0.2483 | 0.2152 | 0.2649 |
| 0.6955        | 28.42 | 540  | 0.6954          | 0.4702   | 0.0066 | 0.4636 | 0.0    | 0.5298 |
| 0.7095        | 29.47 | 560  | 0.6961          | 0.4702   | 0.0066 | 0.4636 | 0.0    | 0.5298 |
| 0.6953        | 30.53 | 580  | 0.6919          | 0.5132   | 0.4371 | 0.0762 | 0.3874 | 0.0993 |
| 0.7124        | 31.58 | 600  | 0.6946          | 0.4834   | 0.0331 | 0.4503 | 0.0132 | 0.5033 |
| 0.6929        | 32.63 | 620  | 0.6936          | 0.5265   | 0.1457 | 0.3808 | 0.0828 | 0.3907 |
| 0.7103        | 33.68 | 640  | 0.6926          | 0.5265   | 0.3477 | 0.1788 | 0.2848 | 0.1887 |
| 0.6993        | 34.74 | 660  | 0.6937          | 0.5166   | 0.1192 | 0.3974 | 0.0662 | 0.4172 |
| 0.6975        | 35.79 | 680  | 0.6936          | 0.5199   | 0.1291 | 0.3907 | 0.0728 | 0.4073 |
| 0.6935        | 36.84 | 700  | 0.6937          | 0.5199   | 0.1026 | 0.4172 | 0.0464 | 0.4338 |
| 0.7039        | 37.89 | 720  | 0.6925          | 0.5232   | 0.3642 | 0.1589 | 0.3046 | 0.1722 |
| 0.6999        | 38.95 | 740  | 0.6941          | 0.5099   | 0.0662 | 0.4437 | 0.0199 | 0.4702 |
| 0.6965        | 40.0  | 760  | 0.6948          | 0.4735   | 0.0166 | 0.4570 | 0.0066 | 0.5199 |
| 0.7039        | 41.05 | 780  | 0.6944          | 0.4934   | 0.0430 | 0.4503 | 0.0132 | 0.4934 |
| 0.7026        | 42.11 | 800  | 0.6939          | 0.5199   | 0.0795 | 0.4404 | 0.0232 | 0.4570 |
| 0.7072        | 43.16 | 820  | 0.6930          | 0.5199   | 0.2781 | 0.2417 | 0.2219 | 0.2583 |
| 0.7064        | 44.21 | 840  | 0.6930          | 0.5199   | 0.2781 | 0.2417 | 0.2219 | 0.2583 |
| 0.6982        | 45.26 | 860  | 0.6933          | 0.5199   | 0.2119 | 0.3079 | 0.1556 | 0.3245 |
| 0.6921        | 46.32 | 880  | 0.6935          | 0.5232   | 0.1490 | 0.3742 | 0.0894 | 0.3874 |
| 0.6983        | 47.37 | 900  | 0.6939          | 0.5199   | 0.0762 | 0.4437 | 0.0199 | 0.4603 |
| 0.6938        | 48.42 | 920  | 0.6940          | 0.5132   | 0.0695 | 0.4437 | 0.0199 | 0.4669 |
| 0.6984        | 49.47 | 940  | 0.6940          | 0.5132   | 0.0695 | 0.4437 | 0.0199 | 0.4669 |


### Framework versions

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