metadata

license: apache-2.0
base_model: alex-miller/ODABert
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: iati-drr-classifier
    results: []
datasets:
  - alex-miller/iati-policy-markers
pipeline_tag: text-classification
widget:
  - text: >-
      Core pandemic preparedness and response and integrated global health
      priorities
    example_title: Positive
  - text: >-
      Education programs for the disabled and access to learning opportunities
      for children
    example_title: Negative

iati-drr-classifier

This model is a fine-tuned version of alex-miller/ODABert on a subset of the alex-miller/iati-policy-markers dataset. It achieves the following results on the evaluation set:

Loss: 0.3910
Accuracy: 0.8207

Model description

This model has been trained to identify disaster risk reduction (DRR) project titles and/or descriptions. It returns "0" for projects with no DRR component, and "1" for projects with DRR as a principal or significant objective.

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Code to subset the dataset and train the model is available here.

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 1e-06
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.607	1.0	508	0.5053	0.7507
0.4569	2.0	1016	0.4289	0.7980
0.4011	3.0	1524	0.4009	0.8143
0.3786	4.0	2032	0.3910	0.8207

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2