scandi-fine-web-cleaner

This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the data-is-better-together/fineweb-c dataset. It achieves the following results on the evaluation set:

• Loss: 0.1816
• Precision: 0.9524
• Recall: 0.7018
• F1: 0.8081
• Auc Roc: 0.9648
• Balanced Accuracy: 0.8480
• Average Precision: 0.8906

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: 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
• num_epochs: 10
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Auc Roc	Balanced Accuracy	Average Precision
0.3165	1.0	100	0.2333	0.95	0.6667	0.7835	0.8099	0.8304	0.7721
0.1929	2.0	200	0.1359	0.9130	0.7368	0.8155	0.9778	0.8626	0.9105
0.1775	3.0	300	0.2245	0.9268	0.6667	0.7755	0.9481	0.8290	0.8721
0.1553	4.0	400	0.1816	0.9524	0.7018	0.8081	0.9648	0.8480	0.8906

Framework versions

• Transformers 4.48.0
• Pytorch 2.5.1+cu124
• Datasets 3.2.0
• Tokenizers 0.21.0