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
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Model tree for alex-miller/iati-drr-classifier
Base model
google-bert/bert-base-multilingual-uncased
Finetuned
alex-miller/ODABert