--- 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: [] 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." --- # distil-bert-fintuned-issues-cfpb-complaints This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.6711 - Accuracy: 0.7652 - Precision: 0.5935 - Recall: 0.5577 - F1: 0.5702 ## 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: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:| | 0.7269 | 1.0 | 11603 | 0.7187 | 0.7438 | 0.5853 | 0.5327 | 0.5491 | | 0.612 | 2.0 | 23206 | 0.6711 | 0.7652 | 0.5935 | 0.5577 | 0.5702 | ### Framework versions - Transformers 4.37.2 - Pytorch 2.2.0 - Datasets 2.17.1 - Tokenizers 0.15.2