---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: distil-bert-fintuned-subissue-cfpb-complaints
  results: []
widget:
- text : "it is absurd that i have consistently made timely payments for this account and have never been overdue. i kindly request that you promptly update my account to reflect this accurately."
---
---

<!-- 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. -->

# distil-bert-fintuned-subissue-cfpb-complaints

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the Consumer Financial Protection Bureau(CFPB) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9809
- Accuracy: 0.7110
- Precision: 0.4293
- Recall: 0.3614
- F1: 0.3474

## 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: 2e-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: 1

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.998         | 1.0   | 11603 | 0.9809          | 0.7110   | 0.4293    | 0.3614 | 0.3474 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.17.1
- Tokenizers 0.15.2