xlm-roberta-product-extractor-v3

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

• Loss: 0.4646
• F1: 0.5228

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: 3e-05
• train_batch_size: 16
• eval_batch_size: 8
• 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
• num_epochs: 10
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1
No log	1.0	111	0.3273	0.4197
No log	2.0	222	0.3069	0.4501
No log	3.0	333	0.3227	0.4843
No log	4.0	444	0.3350	0.4872
0.2578	5.0	555	0.3472	0.5192
0.2578	6.0	666	0.4177	0.5211
0.2578	7.0	777	0.4221	0.5000
0.2578	8.0	888	0.4393	0.5
0.2578	9.0	999	0.4462	0.4977
0.0984	10.0	1110	0.4646	0.5228

Framework versions

• Transformers 4.57.3
• Pytorch 2.8.0+cu128
• Datasets 4.3.0
• Tokenizers 0.22.1