---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: bert-sdg-classification
  results: []
datasets:
- albertmartinez/OSDG
pipeline_tag: text-classification
---

<!-- 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-sdg-classification

This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7055
- F1: 0.7980

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 600
- num_epochs: 5.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.2299        | 1.0   | 538  | 1.0520          | 0.7118 |
| 0.9383        | 2.0   | 1076 | 0.7800          | 0.7794 |
| 0.7379        | 3.0   | 1614 | 0.7253          | 0.7947 |
| 0.6362        | 4.0   | 2152 | 0.7107          | 0.7965 |
| 0.5779        | 5.0   | 2690 | 0.7055          | 0.7980 |


### Framework versions

- Transformers 4.49.0.dev0
- Pytorch 2.1.2.post304
- Datasets 3.2.0
- Tokenizers 0.21.0