mdeberta-product-ner – AI Model by JamesLemo | AlphaNeural AI

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JamesLemo/
mdeberta-product-ner

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token-classification

generated_from_trainer

microsoft/mdeberta-v3-base

endpoints_compatible

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mdeberta-product-ner

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

Loss: 0.0220
Precision: 0.9801
Recall: 0.9875
F1: 0.9838

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: 5e-06
train_batch_size: 16
eval_batch_size: 16
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_steps: 0.2
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1
0.1390	1.0	1255	0.0768	0.7528	0.8216	0.7857
0.0510	2.0	2510	0.0283	0.9624	0.9698	0.9661
0.0268	3.0	3765	0.0249	0.9729	0.9815	0.9772
0.0211	4.0	5020	0.0226	0.9749	0.9849	0.9799
0.0166	5.0	6275	0.0220	0.9801	0.9875	0.9838

Framework versions

Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2