sdg_1 sdg_10 sdg_11 sdg_12 sdg_13 sdg_14 sdg_15 sdg_2 sdg_3 sdg_4 sdg_5 sdg_6 sdg_7 sdg_8 sdg_9
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-uncased-finetuned-osdg
  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-osdg

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5716
- F1 Score: 0.8359
- Accuracy: 0.8726

## 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: 7e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- 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 | F1 Score | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 0.6505        | 1.0   | 830  | 0.5662          | 0.8140   | 0.8577   |
| 0.4115        | 2.0   | 1660 | 0.5699          | 0.8249   | 0.8625   |
| 0.2334        | 3.0   | 2490 | 0.5716          | 0.8359   | 0.8726   |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
