deberta-v3-base-smart-pricing-regressor

This model is a fine-tuned version of microsoft/deberta-v3-base on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.5495
• Mae: 0.5754

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: 32
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 200
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Mae
0.7715	0.2370	500	0.7129	0.6837
0.6083	0.4740	1000	0.5971	0.6050
0.5801	0.7111	1500	0.5736	0.5892
0.5442	0.9481	2000	0.5833	0.5949
0.567	1.1849	2500	0.5858	0.6013
0.5452	1.4219	3000	0.5495	0.5754
0.542	1.6589	3500	0.5736	0.5922
0.5146	1.8959	4000	0.5731	0.5914

Framework versions

• PEFT 0.16.0
• Transformers 4.53.3
• Pytorch 2.6.0+cu124
• Datasets 4.1.1
• Tokenizers 0.21.2