distilbert_enron_hf_format_ft_v2

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: 0.0056
• Precision: 0.8276
• Recall: 0.9116
• F1: 0.8675
• Accuracy: 0.9980

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	Precision	Recall	F1	Accuracy
0.0389	1.0	594	0.0067	0.8154	0.8854	0.8490	0.9977
0.0063	2.0	1188	0.0056	0.8276	0.9116	0.8675	0.9980

Framework versions

• Transformers 4.31.0
• Pytorch 2.0.1
• Datasets 2.14.6
• Tokenizers 0.13.3