metadata

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-issues-cfpb-complaints
    results: []

distil-bert-fintuned-issues-cfpb-complaints

This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.7196
Accuracy: 0.7450
Precision: 0.5763
Recall: 0.5233
F1: 0.5371

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
0.7281	1.0	11603	0.7196	0.7450	0.5763	0.5233	0.5371

Framework versions

Transformers 4.37.2
Pytorch 2.2.0
Datasets 2.17.1
Tokenizers 0.15.2