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alex-miller/iati-climate-classifier

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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iati-climate-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: 0.2377
  • Accuracy: 0.9138
  • F1: 0.9165
  • Precision: 0.8889
  • Recall: 0.9458

Model description

This model has been trained to identify climate mitigation and climate adaptation project titles and/or descriptions. It returns "0" for projects with no climate component, and "1" for projects with adaptation or mitigation as principal objectives.

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
  • trainbatchsize: 16
  • evalbatchsize: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 7

Training results

Training LossEpochStepValidation LossAccuracyF1PrecisionRecall
0.49921.08760.89210.89780.28310.85300.9475
0.27062.017520.90380.90570.24460.88810.9241
0.24943.026280.90950.91140.23700.89270.9309
0.23934.035040.91120.91400.23850.88630.9435
0.23065.043800.91240.91520.23800.88700.9452
0.2296.052560.24050.91210.91520.88360.9492
0.22557.061320.23770.91380.91650.88890.9458

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2