---
library_name: transformers
license: apache-2.0
base_model: alex-miller/ODABert
tags:
- generated_from_trainer
model-index:
- name: wb-climate-regression
  results: []
datasets:
- alex-miller/wb-climate-percentage
---


# wb-climate-regression

This model is a fine-tuned version of [alex-miller/ODABert](https://huggingface.co/alex-miller/ODABert) on the [alex-miller/wb-climate-percentage](https://huggingface.co/datasets/alex-miller/wb-climate-percentage) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0309

## Model description

A regression model that embeds text using a fine-tuned bert-base-multilingual-uncased and uses the AutoModelForSequenceClassification class to output predicted percentage climate finance, climate adaptation finance, and climate mitigation finance.

## Intended uses & limitations

Intended to regress World Bank project development objectives and abstracts. Not yet validated against project descriptions written outside of the World Bank project API V3.

## Training and evaluation data

Data was collected automatically from the World Bank project API V3. For full code on how data was gathered, see: [https://github.com/akmiller01/world-bank-climate-regression/blob/main/code/wb_api_climate.py](https://github.com/akmiller01/world-bank-climate-regression/blob/main/code/wb_api_climate.py)

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.0722        | 1.0   | 126  | 0.0577          |
| 0.0481        | 2.0   | 252  | 0.0391          |
| 0.04          | 3.0   | 378  | 0.0350          |
| 0.0366        | 4.0   | 504  | 0.0332          |
| 0.0341        | 5.0   | 630  | 0.0323          |
| 0.0323        | 6.0   | 756  | 0.0312          |
| 0.0304        | 7.0   | 882  | 0.0312          |
| 0.0296        | 8.0   | 1008 | 0.0310          |
| 0.0281        | 9.0   | 1134 | 0.0306          |
| 0.0268        | 10.0  | 1260 | 0.0310          |
| 0.0261        | 11.0  | 1386 | 0.0303          |
| 0.0247        | 12.0  | 1512 | 0.0305          |
| 0.0243        | 13.0  | 1638 | 0.0310          |
| 0.0233        | 14.0  | 1764 | 0.0306          |
| 0.0221        | 15.0  | 1890 | 0.0309          |
| 0.0222        | 16.0  | 2016 | 0.0307          |
| 0.0216        | 17.0  | 2142 | 0.0308          |
| 0.0211        | 18.0  | 2268 | 0.0312          |
| 0.021         | 19.0  | 2394 | 0.0310          |
| 0.0206        | 20.0  | 2520 | 0.0309          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1