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distil-bert-fintuned-subissue-cfpb-complaints

This model is a fine-tuned version of 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