---
license: apache-2.0
base_model: alex-miller/ODABert
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: curated-gender-equality-ordinal-weighted
  results: []
---

<!-- 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. -->

# curated-gender-equality-ordinal-weighted

This model is a fine-tuned version of [alex-miller/ODABert](https://huggingface.co/alex-miller/ODABert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1956
- Accuracy: 0.9603
- F1: 0.9485
- Precision: 0.9288
- Recall: 0.9690

## 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: 1e-06
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.653         | 1.0   | 342  | 0.4418          | 0.7789   | 0.7700 | 0.6341    | 0.9800 |
| 0.3746        | 2.0   | 684  | 0.3035          | 0.9164   | 0.8967 | 0.8403    | 0.9613 |
| 0.2861        | 3.0   | 1026 | 0.2572          | 0.9425   | 0.9268 | 0.8919    | 0.9645 |
| 0.2451        | 4.0   | 1368 | 0.2372          | 0.9449   | 0.9297 | 0.8968    | 0.9651 |
| 0.2205        | 5.0   | 1710 | 0.2252          | 0.9483   | 0.9340 | 0.9020    | 0.9684 |
| 0.2019        | 6.0   | 2052 | 0.2159          | 0.9488   | 0.9347 | 0.9021    | 0.9697 |
| 0.1881        | 7.0   | 2394 | 0.2091          | 0.9520   | 0.9384 | 0.9102    | 0.9684 |
| 0.1762        | 8.0   | 2736 | 0.2035          | 0.9551   | 0.9422 | 0.9174    | 0.9684 |
| 0.1699        | 9.0   | 3078 | 0.2052          | 0.9534   | 0.9402 | 0.9125    | 0.9697 |
| 0.1572        | 10.0  | 3420 | 0.1975          | 0.9576   | 0.9452 | 0.9226    | 0.9690 |
| 0.1502        | 11.0  | 3762 | 0.1997          | 0.9576   | 0.9452 | 0.9220    | 0.9697 |
| 0.1451        | 12.0  | 4104 | 0.1934          | 0.9600   | 0.9481 | 0.9293    | 0.9677 |
| 0.1406        | 13.0  | 4446 | 0.1994          | 0.9569   | 0.9444 | 0.9198    | 0.9703 |
| 0.1375        | 14.0  | 4788 | 0.1912          | 0.9612   | 0.9497 | 0.9311    | 0.9690 |
| 0.1321        | 15.0  | 5130 | 0.1943          | 0.9600   | 0.9482 | 0.9288    | 0.9684 |
| 0.1275        | 16.0  | 5472 | 0.1974          | 0.9603   | 0.9485 | 0.9288    | 0.9690 |
| 0.1269        | 17.0  | 5814 | 0.1928          | 0.9610   | 0.9493 | 0.9316    | 0.9677 |
| 0.1264        | 18.0  | 6156 | 0.1924          | 0.9617   | 0.9502 | 0.9334    | 0.9677 |
| 0.1244        | 19.0  | 6498 | 0.1951          | 0.9605   | 0.9488 | 0.9294    | 0.9690 |
| 0.1195        | 20.0  | 6840 | 0.1956          | 0.9603   | 0.9485 | 0.9288    | 0.9690 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1