roberta-base_binary – AI Model by Zlovoblachko | AlphaNeural AI | AlphaNeural AI

You can deploy this model and start earning money today!

Zlovoblachko/
roberta-base_binary

like

0

token-classification

generated_from_trainer

FacebookAI/roberta-base

autotrain_compatible

endpoints_compatible

Views

No views yet

roberta-base_binary

This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1729
Precision: 0.8178
Recall: 0.6136
F1: 0.7012
F0.5: 0.7668
Macro Precision: 0.8824
Macro Recall: 0.7971
Macro F1: 0.8323
Macro F0.5: 0.8602

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: 3e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Use OptimizerNames.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: 2
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	F0.5	Macro Precision	Macro Recall	Macro F1	Macro F0.5
0.1963	1.0	1926	0.1702	0.8148	0.6179	0.7028	0.7660	0.8814	0.7991	0.8333	0.8601
0.1621	1.9992	3850	0.1698	0.8027	0.6472	0.7166	0.7659	0.8772	0.8124	0.8405	0.8613

Framework versions

Transformers 4.50.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1