---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-quora-insincere
  results: []
---

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# distilbert-base-uncased-finetuned-quora-insincere

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on [quora-insincere](https://huggingface.co/datasets/UKPLab/insincere-questions) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0946
- Accuracy: 0.9676
- F1 Score: 0.7309

## Model description

LABEL_0 = Sincere question
LABEL_1 = Insincere question

## 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: 2e-05
- train_batch_size: 20
- eval_batch_size: 20
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 0.093         | 1.0   | 62807  | 0.0859          | 0.9644   |
| 0.0695        | 2.0   | 125614 | 0.0946          | 0.9676   |

### Evaluation results

'eval_loss': 0.09461139887571335,
'eval_accuracy': 0.9676,
'eval_f1': 0.7308970099667774,

### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1