---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- crows_pairs
metrics:
- accuracy
model-index:
- name: multiberts-seed_1_crows_pairs_classifieronly
  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: 0.5331125827814569
---

<!-- 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. -->

# multiberts-seed_1_crows_pairs_classifieronly

This model is a fine-tuned version of [google/multiberts-seed_1](https://huggingface.co/google/multiberts-seed_1) on the crows_pairs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6903
- Accuracy: 0.5331
- Tp: 0.3477
- Tn: 0.1854
- Fp: 0.3146
- Fn: 0.1523

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|
| 0.7016        | 1.05  | 20   | 0.6910          | 0.5364   | 0.4437 | 0.0927 | 0.4073 | 0.0563 |
| 0.7072        | 2.11  | 40   | 0.6914          | 0.5166   | 0.4834 | 0.0331 | 0.4669 | 0.0166 |
| 0.7003        | 3.16  | 60   | 0.6910          | 0.5497   | 0.0927 | 0.4570 | 0.0430 | 0.4073 |
| 0.7004        | 4.21  | 80   | 0.6908          | 0.5265   | 0.2583 | 0.2682 | 0.2318 | 0.2417 |
| 0.6985        | 5.26  | 100  | 0.6916          | 0.5033   | 0.0033 | 0.5    | 0.0    | 0.4967 |
| 0.7107        | 6.32  | 120  | 0.6909          | 0.5364   | 0.4603 | 0.0762 | 0.4238 | 0.0397 |
| 0.7135        | 7.37  | 140  | 0.6908          | 0.5364   | 0.4139 | 0.1225 | 0.3775 | 0.0861 |
| 0.7041        | 8.42  | 160  | 0.6908          | 0.5464   | 0.2848 | 0.2616 | 0.2384 | 0.2152 |
| 0.7022        | 9.47  | 180  | 0.6907          | 0.5298   | 0.2450 | 0.2848 | 0.2152 | 0.2550 |
| 0.6996        | 10.53 | 200  | 0.6908          | 0.5265   | 0.4371 | 0.0894 | 0.4106 | 0.0629 |
| 0.7049        | 11.58 | 220  | 0.6914          | 0.5066   | 0.0066 | 0.5    | 0.0    | 0.4934 |
| 0.6975        | 12.63 | 240  | 0.6912          | 0.5232   | 0.4834 | 0.0397 | 0.4603 | 0.0166 |
| 0.6967        | 13.68 | 260  | 0.6907          | 0.5497   | 0.2748 | 0.2748 | 0.2252 | 0.2252 |
| 0.705         | 14.74 | 280  | 0.6912          | 0.5132   | 0.0132 | 0.5    | 0.0    | 0.4868 |
| 0.6943        | 15.79 | 300  | 0.6909          | 0.5298   | 0.4768 | 0.0530 | 0.4470 | 0.0232 |
| 0.7057        | 16.84 | 320  | 0.6906          | 0.5364   | 0.4272 | 0.1093 | 0.3907 | 0.0728 |
| 0.6995        | 17.89 | 340  | 0.6905          | 0.5530   | 0.2252 | 0.3278 | 0.1722 | 0.2748 |
| 0.6989        | 18.95 | 360  | 0.6905          | 0.5464   | 0.1854 | 0.3609 | 0.1391 | 0.3146 |
| 0.7156        | 20.0  | 380  | 0.6912          | 0.5199   | 0.4834 | 0.0364 | 0.4636 | 0.0166 |
| 0.6957        | 21.05 | 400  | 0.6905          | 0.5497   | 0.2285 | 0.3212 | 0.1788 | 0.2715 |
| 0.6978        | 22.11 | 420  | 0.6906          | 0.5331   | 0.4371 | 0.0960 | 0.4040 | 0.0629 |
| 0.6988        | 23.16 | 440  | 0.6905          | 0.5331   | 0.3179 | 0.2152 | 0.2848 | 0.1821 |
| 0.7054        | 24.21 | 460  | 0.6905          | 0.5497   | 0.1623 | 0.3874 | 0.1126 | 0.3377 |
| 0.6997        | 25.26 | 480  | 0.6907          | 0.5166   | 0.4636 | 0.0530 | 0.4470 | 0.0364 |
| 0.7007        | 26.32 | 500  | 0.6904          | 0.5364   | 0.3940 | 0.1424 | 0.3576 | 0.1060 |
| 0.6973        | 27.37 | 520  | 0.6914          | 0.5      | 0.0    | 0.5    | 0.0    | 0.5    |
| 0.704         | 28.42 | 540  | 0.6905          | 0.5364   | 0.4338 | 0.1026 | 0.3974 | 0.0662 |
| 0.7028        | 29.47 | 560  | 0.6905          | 0.5530   | 0.1192 | 0.4338 | 0.0662 | 0.3808 |
| 0.6959        | 30.53 | 580  | 0.6905          | 0.5364   | 0.4404 | 0.0960 | 0.4040 | 0.0596 |
| 0.704         | 31.58 | 600  | 0.6904          | 0.5464   | 0.2583 | 0.2881 | 0.2119 | 0.2417 |
| 0.704         | 32.63 | 620  | 0.6903          | 0.5397   | 0.3146 | 0.2252 | 0.2748 | 0.1854 |
| 0.7003        | 33.68 | 640  | 0.6903          | 0.5430   | 0.3079 | 0.2351 | 0.2649 | 0.1921 |
| 0.7058        | 34.74 | 660  | 0.6903          | 0.5464   | 0.3079 | 0.2384 | 0.2616 | 0.1921 |
| 0.7095        | 35.79 | 680  | 0.6903          | 0.5430   | 0.2649 | 0.2781 | 0.2219 | 0.2351 |
| 0.7019        | 36.84 | 700  | 0.6905          | 0.5397   | 0.0695 | 0.4702 | 0.0298 | 0.4305 |
| 0.7167        | 37.89 | 720  | 0.6907          | 0.5099   | 0.0166 | 0.4934 | 0.0066 | 0.4834 |
| 0.6975        | 38.95 | 740  | 0.6903          | 0.5497   | 0.3113 | 0.2384 | 0.2616 | 0.1887 |
| 0.7036        | 40.0  | 760  | 0.6903          | 0.5397   | 0.3311 | 0.2086 | 0.2914 | 0.1689 |
| 0.7009        | 41.05 | 780  | 0.6903          | 0.5331   | 0.3940 | 0.1391 | 0.3609 | 0.1060 |
| 0.7004        | 42.11 | 800  | 0.6903          | 0.5430   | 0.2980 | 0.2450 | 0.2550 | 0.2020 |
| 0.699         | 43.16 | 820  | 0.6903          | 0.5430   | 0.2152 | 0.3278 | 0.1722 | 0.2848 |
| 0.6962        | 44.21 | 840  | 0.6903          | 0.5430   | 0.2980 | 0.2450 | 0.2550 | 0.2020 |
| 0.6981        | 45.26 | 860  | 0.6903          | 0.5397   | 0.3543 | 0.1854 | 0.3146 | 0.1457 |
| 0.7008        | 46.32 | 880  | 0.6903          | 0.5430   | 0.3808 | 0.1623 | 0.3377 | 0.1192 |
| 0.7048        | 47.37 | 900  | 0.6903          | 0.5530   | 0.3742 | 0.1788 | 0.3212 | 0.1258 |
| 0.707         | 48.42 | 920  | 0.6903          | 0.5497   | 0.3709 | 0.1788 | 0.3212 | 0.1291 |
| 0.7014        | 49.47 | 940  | 0.6903          | 0.5331   | 0.3477 | 0.1854 | 0.3146 | 0.1523 |


### Framework versions

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