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

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# 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