resultats_roberta_crypto – AI Model by regraisamia | AlphaNeural AI

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regraisamia/
resultats_roberta_crypto

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text-classification

generated_from_trainer

FacebookAI/roberta-base

endpoints_compatible

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resultats_roberta_crypto

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

Loss: 0.4595
Accuracy: 0.8559
F1: 0.8559
Precision: 0.8561
Recall: 0.8559

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_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_steps: 500
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.7586	1.0	804	0.4281	0.8343	0.8347	0.8375	0.8343
0.3697	2.0	1608	0.4615	0.8396	0.8388	0.8410	0.8396
0.2795	3.0	2412	0.4595	0.8559	0.8559	0.8561	0.8559
0.1881	4.0	3216	0.5545	0.8554	0.8553	0.8555	0.8554

Framework versions

Transformers 4.57.6
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.2