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metadata
license: apache-2.0
tags:
  - generated_from_trainer
model-index:
  - name: bert-base-uncased-finetuned-sdg
    results: []

bert-base-uncased-finetuned-sdg

This model is a fine-tuned version of bert-base-uncased on the OSDG dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3094
  • Acc: 0.9195

Model description

Classifies text to the first 16 SDGs!

Intended uses & limitations

Assess policy documents, classify text to SDGs, etc.

Training and evaluation data

OSDG data. Updated version from October.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0001
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 42
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Acc
0.3768 1.0 269 0.3758 0.8933
0.2261 2.0 538 0.3088 0.9095
0.1038 3.0 807 0.3094 0.9195

Framework versions

  • Transformers 4.23.1
  • Pytorch 1.12.0a0+8a1a93a
  • Datasets 2.5.2
  • Tokenizers 0.13.1