ami-addressee-distilbert

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.3827
• Auc: 0.9268

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: 32
• eval_batch_size: 64
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Auc
0.2603	1.0	898	0.3613	0.9199
0.2435	2.0	1796	0.3718	0.9293
0.2624	3.0	2694	0.3827	0.9268

Framework versions

• Transformers 4.57.6
• Pytorch 2.14.0+cu130
• Datasets 5.0.1
• Tokenizers 0.22.2