| --- |
| 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 |
| |
