readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: bert-base-uncased-finetuned-sdg
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # bert-base-uncased-finetuned-sdg
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/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
  