XLM-RoBERTa-CERED3

stulcrad/XLM-RoBERTa-CERED3

XLM-RoBERTa-CERED3 is a machine learning model from stulcrad. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.

should probably proofread and complete it, then remove this comment. --

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At a glance

Library: transformers
License: mit
Model type: xlm-roberta
Access: Public
Created: Mar 21, 2025
Updated: Jun 26, 2025
SHA: e8759f18

Base models

Datasets

generator

Model card

From the Hugging Face model README

XLM-RoBERTa-CERED3

This model is a fine-tuned version of xlm-roberta-large on the generator dataset. It achieves the following results on the evaluation set:

Loss: 0.7170
Accuracy: 0.8504
Micro Precision: 0.8504
Micro Recall: 0.8504
Micro F1: 0.8504
Macro Precision: 0.8385
Macro Recall: 0.8215
Macro F1: 0.8214

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: 1e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Use 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: 1000
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Micro Precision	Micro Recall	Micro F1	Macro Precision	Macro Recall	Macro F1
0.7716	1.0	4758	0.6650	0.8018	0.8018	0.8018	0.8018	0.7651	0.7657	0.7439
0.6058	2.0	9516	0.5986	0.8134	0.8134	0.8134	0.8134	0.7845	0.7729	0.7606
0.5039	3.0	14274	0.5782	0.8302	0.8302	0.8302	0.8302	0.8169	0.7916	0.7843
0.4162	4.0	19032	0.5908	0.8359	0.8359	0.8359	0.8359	0.8184	0.8019	0.7983
0.3485	5.0	23790	0.5714	0.8431	0.8431	0.8431	0.8431	0.8218	0.7982	0.7977
0.2865	6.0	28548	0.5836	0.8516	0.8516	0.8516	0.8516	0.8207	0.8194	0.8118
0.2435	7.0	33306	0.6007	0.8523	0.8523	0.8523	0.8523	0.8335	0.8279	0.8213
0.2088	8.0	38064	0.6433	0.8520	0.8520	0.8520	0.8520	0.8274	0.8232	0.8155
0.164	9.0	42822	0.6642	0.8503	0.8503	0.8503	0.8503	0.8261	0.8221	0.8140
0.1369	10.0	47580	0.6762	0.8537	0.8537	0.8537	0.8537	0.8333	0.8271	0.8217

Framework versions

Transformers 4.46.2
Pytorch 2.5.1+cu124
Datasets 3.1.0
Tokenizers 0.20.3

Library: transformers
Type: xlm-roberta
License: mit
Created: Mar 21, 2025
Updated: Jun 26, 2025