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---
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 |