---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- crows_pairs
metrics:
- accuracy
model-index:
- name: t5-small_crows_pairs_finetuned
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: crows_pairs
      type: crows_pairs
      config: crows_pairs
      split: test
      args: crows_pairs
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5827814569536424
---

<!-- 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. -->

# t5-small_crows_pairs_finetuned

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the crows_pairs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5333
- Accuracy: 0.5828
- Tp: 0.4967
- Tn: 0.0861
- Fp: 0.4106
- Fn: 0.0066

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|
| 4.1732        | 1.05  | 20   | 2.2158          | 0.8245   | 0.4404 | 0.3841 | 0.1126 | 0.0629 |
| 0.6547        | 2.11  | 40   | 0.4472          | 0.5033   | 0.5033 | 0.0    | 0.4967 | 0.0    |
| 0.4173        | 3.16  | 60   | 0.3662          | 0.5033   | 0.5033 | 0.0    | 0.4967 | 0.0    |
| 0.3822        | 4.21  | 80   | 0.3529          | 0.5033   | 0.5033 | 0.0    | 0.4967 | 0.0    |
| 0.394         | 5.26  | 100  | 0.3584          | 0.5033   | 0.5033 | 0.0    | 0.4967 | 0.0    |
| 0.36          | 6.32  | 120  | 0.3446          | 0.5033   | 0.5033 | 0.0    | 0.4967 | 0.0    |
| 0.3472        | 7.37  | 140  | 0.3410          | 0.5033   | 0.5033 | 0.0    | 0.4967 | 0.0    |
| 0.3241        | 8.42  | 160  | 0.3369          | 0.5033   | 0.5033 | 0.0    | 0.4967 | 0.0    |
| 0.3247        | 9.47  | 180  | 0.3252          | 0.5033   | 0.5033 | 0.0    | 0.4967 | 0.0    |
| 0.3045        | 10.53 | 200  | 0.3152          | 0.5033   | 0.5033 | 0.0    | 0.4967 | 0.0    |
| 0.2863        | 11.58 | 220  | 0.3034          | 0.5232   | 0.5033 | 0.0199 | 0.4768 | 0.0    |
| 0.2462        | 12.63 | 240  | 0.2958          | 0.5232   | 0.5033 | 0.0199 | 0.4768 | 0.0    |
| 0.2151        | 13.68 | 260  | 0.2988          | 0.5232   | 0.5033 | 0.0199 | 0.4768 | 0.0    |
| 0.2323        | 14.74 | 280  | 0.2964          | 0.5397   | 0.5033 | 0.0364 | 0.4603 | 0.0    |
| 0.1951        | 15.79 | 300  | 0.2994          | 0.5430   | 0.5033 | 0.0397 | 0.4570 | 0.0    |
| 0.1848        | 16.84 | 320  | 0.3049          | 0.5530   | 0.5033 | 0.0497 | 0.4470 | 0.0    |
| 0.1875        | 17.89 | 340  | 0.3117          | 0.5596   | 0.5033 | 0.0563 | 0.4404 | 0.0    |
| 0.1646        | 18.95 | 360  | 0.3291          | 0.5596   | 0.5033 | 0.0563 | 0.4404 | 0.0    |
| 0.1622        | 20.0  | 380  | 0.3341          | 0.5563   | 0.5033 | 0.0530 | 0.4437 | 0.0    |
| 0.1511        | 21.05 | 400  | 0.3415          | 0.5596   | 0.5033 | 0.0563 | 0.4404 | 0.0    |
| 0.1497        | 22.11 | 420  | 0.3556          | 0.5629   | 0.5033 | 0.0596 | 0.4371 | 0.0    |
| 0.1195        | 23.16 | 440  | 0.3717          | 0.5563   | 0.5033 | 0.0530 | 0.4437 | 0.0    |
| 0.1319        | 24.21 | 460  | 0.3753          | 0.5662   | 0.5033 | 0.0629 | 0.4338 | 0.0    |
| 0.1099        | 25.26 | 480  | 0.3812          | 0.5728   | 0.5033 | 0.0695 | 0.4272 | 0.0    |
| 0.1078        | 26.32 | 500  | 0.3879          | 0.5695   | 0.5033 | 0.0662 | 0.4305 | 0.0    |
| 0.091         | 27.37 | 520  | 0.4009          | 0.5762   | 0.5    | 0.0762 | 0.4205 | 0.0033 |
| 0.0939        | 28.42 | 540  | 0.4204          | 0.5795   | 0.5    | 0.0795 | 0.4172 | 0.0033 |
| 0.1011        | 29.47 | 560  | 0.4295          | 0.5828   | 0.5    | 0.0828 | 0.4139 | 0.0033 |
| 0.0871        | 30.53 | 580  | 0.4336          | 0.5762   | 0.5    | 0.0762 | 0.4205 | 0.0033 |
| 0.0782        | 31.58 | 600  | 0.4421          | 0.5762   | 0.5    | 0.0762 | 0.4205 | 0.0033 |
| 0.0842        | 32.63 | 620  | 0.4455          | 0.5762   | 0.5    | 0.0762 | 0.4205 | 0.0033 |
| 0.0779        | 33.68 | 640  | 0.4588          | 0.5828   | 0.4967 | 0.0861 | 0.4106 | 0.0066 |
| 0.0684        | 34.74 | 660  | 0.4728          | 0.5795   | 0.4967 | 0.0828 | 0.4139 | 0.0066 |
| 0.0719        | 35.79 | 680  | 0.4747          | 0.5828   | 0.4967 | 0.0861 | 0.4106 | 0.0066 |
| 0.0754        | 36.84 | 700  | 0.4822          | 0.5795   | 0.4967 | 0.0828 | 0.4139 | 0.0066 |
| 0.0622        | 37.89 | 720  | 0.4887          | 0.5795   | 0.4967 | 0.0828 | 0.4139 | 0.0066 |
| 0.0604        | 38.95 | 740  | 0.4963          | 0.5795   | 0.4967 | 0.0828 | 0.4139 | 0.0066 |
| 0.0592        | 40.0  | 760  | 0.5034          | 0.5828   | 0.4967 | 0.0861 | 0.4106 | 0.0066 |
| 0.0621        | 41.05 | 780  | 0.5099          | 0.5795   | 0.4967 | 0.0828 | 0.4139 | 0.0066 |
| 0.0548        | 42.11 | 800  | 0.5151          | 0.5861   | 0.4967 | 0.0894 | 0.4073 | 0.0066 |
| 0.0653        | 43.16 | 820  | 0.5197          | 0.5795   | 0.4967 | 0.0828 | 0.4139 | 0.0066 |
| 0.0593        | 44.21 | 840  | 0.5238          | 0.5795   | 0.4967 | 0.0828 | 0.4139 | 0.0066 |
| 0.0445        | 45.26 | 860  | 0.5287          | 0.5795   | 0.4967 | 0.0828 | 0.4139 | 0.0066 |
| 0.0541        | 46.32 | 880  | 0.5298          | 0.5828   | 0.4967 | 0.0861 | 0.4106 | 0.0066 |
| 0.0578        | 47.37 | 900  | 0.5318          | 0.5795   | 0.4967 | 0.0828 | 0.4139 | 0.0066 |
| 0.0514        | 48.42 | 920  | 0.5330          | 0.5828   | 0.4967 | 0.0861 | 0.4106 | 0.0066 |
| 0.0451        | 49.47 | 940  | 0.5333          | 0.5828   | 0.4967 | 0.0861 | 0.4106 | 0.0066 |


### Framework versions

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