xlm-roberta-base-arq-noaug – AI Model by Kuongan | AlphaNeural AI

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Kuongan/
xlm-roberta-base-arq-noaug

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text-classification

generated_from_trainer

FacebookAI/xlm-roberta-base

autotrain_compatible

endpoints_compatible

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xlm-roberta-base-arq-noaug

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: 0.6397
F1: 0.2220
Roc Auc: 0.5286
Accuracy: 0.06

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: 32
eval_batch_size: 32
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 100
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.7064	1.0	29	0.6397	0.2220	0.5286	0.06
0.6543	2.0	58	0.5791	0.0	0.5	0.12
0.5972	3.0	87	0.5828	0.0	0.5	0.12
0.5807	4.0	116	0.5855	0.0	0.5	0.12
0.5859	5.0	145	0.5686	0.0272	0.5050	0.13

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0