---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-truthful
  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. -->

# distilbert-base-uncased-finetuned-truthful

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4660
- Accuracy: 0.87
- F1: 0.8697

## 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: 9.910294163459086e-05
- train_batch_size: 400
- eval_batch_size: 400
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 9

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 5    | 0.6509          | 0.59     | 0.5780 |
| No log        | 2.0   | 10   | 0.4950          | 0.77     | 0.7701 |
| No log        | 3.0   | 15   | 0.4787          | 0.81     | 0.8099 |
| No log        | 4.0   | 20   | 0.4936          | 0.81     | 0.8096 |
| No log        | 5.0   | 25   | 0.4443          | 0.82     | 0.82   |
| No log        | 6.0   | 30   | 0.4547          | 0.85     | 0.8497 |
| No log        | 7.0   | 35   | 0.4268          | 0.85     | 0.8500 |
| No log        | 8.0   | 40   | 0.4790          | 0.87     | 0.8697 |
| No log        | 9.0   | 45   | 0.4660          | 0.87     | 0.8697 |


### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.1
- Datasets 2.0.0
- Tokenizers 0.11.0
