StanceNakba-EXP4 – AI Model by aomar85 | AlphaNeural AI

You can deploy this model and start earning money today!

aomar85/
StanceNakba-EXP4

like

0

text-classification

generated_from_trainer

UBC-NLP/MARBERTv2

text-embeddings-inference

endpoints_compatible

Views

No views yet

Marbert_concatenatewithPrompt-fold4

This model is a fine-tuned version of UBC-NLP/MARBERTv2 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.4593
Accuracy: 0.8512
Macro F1: 0.8513
Weighted F1: 0.8511
F1 Pro: 0.8772
F1 Against: 0.8276
F1 Neutral: 0.8491

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
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
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Macro F1	Weighted F1	F1 Pro	F1 Against	F1 Neutral
1.0382	1.1628	50	0.7479	0.75	0.7498	0.7488	0.8077	0.6857	0.7559
0.6566	2.3256	100	0.5272	0.8333	0.8312	0.8302	0.8644	0.7843	0.8448
0.4143	3.4884	150	0.4593	0.8512	0.8513	0.8511	0.8772	0.8276	0.8491
0.2816	4.6512	200	0.4628	0.8393	0.8393	0.8389	0.875	0.8036	0.8393

Framework versions

Transformers 4.57.6
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.2