roberta-asap-aes-cv-fold3

BaturalpKorpe/roberta-asap-aes-cv-fold3

roberta-asap-aes-cv-fold3 is a machine learning model from BaturalpKorpe. 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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Public

Updated Dec 19, 2025

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At a glance

Library: transformers
License: mit
Access: Public
Created: Dec 19, 2025
Updated: Dec 19, 2025
SHA: c8d45af7

Base models

Model card

From the Hugging Face model README

roberta-asap-aes-cv-fold3

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

Loss: 0.0173
Qwk Meanfisher: 0.7699
Rmse: 1.5442

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: 2.9950908657191678e-05
train_batch_size: 1
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 4
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_ratio: 0.1878777696731208
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk Meanfisher	Rmse
0.0372	1.0	1947	0.0291	0.6546	2.2192
0.0203	2.0	3894	0.0178	0.7470	1.5064
0.0104	3.0	5841	0.0173	0.7699	1.5442

Framework versions

Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1

Library: transformers
License: mit
Created: Dec 19, 2025
Updated: Dec 19, 2025