---
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: 0.7218543046357616
---

<!-- 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: 1.0876
- Accuracy: 0.7219
- Tp: 0.4901
- Tn: 0.2318
- Fp: 0.2649
- Fn: 0.0132

## 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: 0.0005
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Tp     | Tn     | Fp     | Fn     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|
| 0.4776        | 0.53  | 20   | 0.3559          | 0.5033   | 0.5033 | 0.0    | 0.4967 | 0.0    |
| 0.3708        | 1.05  | 40   | 0.3431          | 0.5265   | 0.5033 | 0.0232 | 0.4735 | 0.0    |
| 0.3905        | 1.58  | 60   | 0.3414          | 0.6325   | 0.5033 | 0.1291 | 0.3675 | 0.0    |
| 0.3526        | 2.11  | 80   | 0.3260          | 0.5464   | 0.5033 | 0.0430 | 0.4536 | 0.0    |
| 0.2734        | 2.63  | 100  | 0.3047          | 0.8179   | 0.4934 | 0.3245 | 0.1722 | 0.0099 |
| 0.2429        | 3.16  | 120  | 0.2631          | 0.6623   | 0.5033 | 0.1589 | 0.3377 | 0.0    |
| 0.2161        | 3.68  | 140  | 0.2829          | 0.7152   | 0.4901 | 0.2252 | 0.2715 | 0.0132 |
| 0.1617        | 4.21  | 160  | 0.2947          | 0.7748   | 0.4901 | 0.2848 | 0.2119 | 0.0132 |
| 0.1776        | 4.74  | 180  | 0.3258          | 0.7384   | 0.4901 | 0.2483 | 0.2483 | 0.0132 |
| 0.1113        | 5.26  | 200  | 0.3362          | 0.7815   | 0.4901 | 0.2914 | 0.2053 | 0.0132 |
| 0.1008        | 5.79  | 220  | 0.4016          | 0.7748   | 0.4868 | 0.2881 | 0.2086 | 0.0166 |
| 0.0572        | 6.32  | 240  | 0.4486          | 0.7219   | 0.4901 | 0.2318 | 0.2649 | 0.0132 |
| 0.0701        | 6.84  | 260  | 0.4561          | 0.7384   | 0.4901 | 0.2483 | 0.2483 | 0.0132 |
| 0.051         | 7.37  | 280  | 0.4813          | 0.7815   | 0.4868 | 0.2947 | 0.2020 | 0.0166 |
| 0.0408        | 7.89  | 300  | 0.5279          | 0.7815   | 0.4868 | 0.2947 | 0.2020 | 0.0166 |
| 0.0326        | 8.42  | 320  | 0.6454          | 0.7550   | 0.4934 | 0.2616 | 0.2351 | 0.0099 |
| 0.0361        | 8.95  | 340  | 0.7559          | 0.7417   | 0.4901 | 0.2517 | 0.2450 | 0.0132 |
| 0.0304        | 9.47  | 360  | 0.7422          | 0.7318   | 0.4868 | 0.2450 | 0.2517 | 0.0166 |
| 0.0299        | 10.0  | 380  | 0.7770          | 0.7450   | 0.4868 | 0.2583 | 0.2384 | 0.0166 |
| 0.0227        | 10.53 | 400  | 0.7033          | 0.7947   | 0.4801 | 0.3146 | 0.1821 | 0.0232 |
| 0.017         | 11.05 | 420  | 0.7220          | 0.7649   | 0.4801 | 0.2848 | 0.2119 | 0.0232 |
| 0.0166        | 11.58 | 440  | 0.7674          | 0.7649   | 0.4636 | 0.3013 | 0.1954 | 0.0397 |
| 0.0123        | 12.11 | 460  | 0.8153          | 0.7616   | 0.4834 | 0.2781 | 0.2185 | 0.0199 |
| 0.0084        | 12.63 | 480  | 0.8422          | 0.7483   | 0.4834 | 0.2649 | 0.2318 | 0.0199 |
| 0.0178        | 13.16 | 500  | 0.7960          | 0.7649   | 0.4735 | 0.2914 | 0.2053 | 0.0298 |
| 0.016         | 13.68 | 520  | 0.8152          | 0.7086   | 0.4834 | 0.2252 | 0.2715 | 0.0199 |
| 0.007         | 14.21 | 540  | 0.8518          | 0.6589   | 0.4901 | 0.1689 | 0.3278 | 0.0132 |
| 0.0019        | 14.74 | 560  | 0.8647          | 0.7020   | 0.4834 | 0.2185 | 0.2781 | 0.0199 |
| 0.0159        | 15.26 | 580  | 0.8817          | 0.7086   | 0.4834 | 0.2252 | 0.2715 | 0.0199 |
| 0.0016        | 15.79 | 600  | 0.9105          | 0.6689   | 0.4834 | 0.1854 | 0.3113 | 0.0199 |
| 0.0079        | 16.32 | 620  | 0.9311          | 0.7053   | 0.4834 | 0.2219 | 0.2748 | 0.0199 |
| 0.0045        | 16.84 | 640  | 0.9586          | 0.7086   | 0.4834 | 0.2252 | 0.2715 | 0.0199 |
| 0.0033        | 17.37 | 660  | 0.9765          | 0.7252   | 0.4834 | 0.2417 | 0.2550 | 0.0199 |
| 0.0078        | 17.89 | 680  | 1.0263          | 0.7086   | 0.4834 | 0.2252 | 0.2715 | 0.0199 |
| 0.0047        | 18.42 | 700  | 0.9929          | 0.7351   | 0.4768 | 0.2583 | 0.2384 | 0.0265 |
| 0.0082        | 18.95 | 720  | 1.0001          | 0.7185   | 0.4801 | 0.2384 | 0.2583 | 0.0232 |
| 0.0022        | 19.47 | 740  | 1.0150          | 0.7086   | 0.4801 | 0.2285 | 0.2682 | 0.0232 |
| 0.0027        | 20.0  | 760  | 1.0638          | 0.6887   | 0.4901 | 0.1987 | 0.2980 | 0.0132 |
| 0.0025        | 20.53 | 780  | 1.0124          | 0.7020   | 0.4834 | 0.2185 | 0.2781 | 0.0199 |
| 0.007         | 21.05 | 800  | 1.0082          | 0.6987   | 0.4834 | 0.2152 | 0.2815 | 0.0199 |
| 0.0119        | 21.58 | 820  | 1.0225          | 0.7119   | 0.4801 | 0.2318 | 0.2649 | 0.0232 |
| 0.0016        | 22.11 | 840  | 1.0494          | 0.7053   | 0.4901 | 0.2152 | 0.2815 | 0.0132 |
| 0.0007        | 22.63 | 860  | 1.0515          | 0.7152   | 0.4868 | 0.2285 | 0.2682 | 0.0166 |
| 0.0014        | 23.16 | 880  | 1.0492          | 0.7119   | 0.4868 | 0.2252 | 0.2715 | 0.0166 |
| 0.002         | 23.68 | 900  | 1.0970          | 0.7020   | 0.4934 | 0.2086 | 0.2881 | 0.0099 |
| 0.0003        | 24.21 | 920  | 1.0429          | 0.7185   | 0.4834 | 0.2351 | 0.2616 | 0.0199 |
| 0.0002        | 24.74 | 940  | 1.0772          | 0.7053   | 0.4868 | 0.2185 | 0.2781 | 0.0166 |
| 0.0008        | 25.26 | 960  | 1.0766          | 0.7119   | 0.4934 | 0.2185 | 0.2781 | 0.0099 |
| 0.001         | 25.79 | 980  | 1.0720          | 0.7185   | 0.4934 | 0.2252 | 0.2715 | 0.0099 |
| 0.0002        | 26.32 | 1000 | 1.0763          | 0.7152   | 0.4901 | 0.2252 | 0.2715 | 0.0132 |
| 0.0002        | 26.84 | 1020 | 1.0675          | 0.7185   | 0.4901 | 0.2285 | 0.2682 | 0.0132 |
| 0.0011        | 27.37 | 1040 | 1.0745          | 0.7185   | 0.4834 | 0.2351 | 0.2616 | 0.0199 |
| 0.0007        | 27.89 | 1060 | 1.0792          | 0.7185   | 0.4901 | 0.2285 | 0.2682 | 0.0132 |
| 0.0007        | 28.42 | 1080 | 1.0880          | 0.7152   | 0.4934 | 0.2219 | 0.2748 | 0.0099 |
| 0.0005        | 28.95 | 1100 | 1.0903          | 0.7185   | 0.4934 | 0.2252 | 0.2715 | 0.0099 |
| 0.0025        | 29.47 | 1120 | 1.0877          | 0.7185   | 0.4901 | 0.2285 | 0.2682 | 0.0132 |
| 0.0004        | 30.0  | 1140 | 1.0876          | 0.7219   | 0.4901 | 0.2318 | 0.2649 | 0.0132 |


### Framework versions

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