roberta – AI Model by Rasmy | AlphaNeural AI

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Rasmy/
roberta

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text-classification

generated_from_trainer

FacebookAI/roberta-base

autotrain_compatible

endpoints_compatible

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roberta

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

Loss: 1.0480
F1: 0.6518
Precision: 0.6478
Recall: 0.6755
Accuracy: 0.6755

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: 4e-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: linear
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Precision	Recall	Accuracy
1.1301	1.0	4409	1.0908	0.6331	0.6205	0.6767	0.6767
0.9143	2.0	8818	1.0480	0.6518	0.6478	0.6755	0.6755
0.7126	3.0	13227	1.2204	0.6456	0.6351	0.6609	0.6609
0.5437	4.0	17636	1.3307	0.6394	0.6304	0.6515	0.6515

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0