bea-2way-full – AI Model by khaled44 | AlphaNeural AI

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khaled44/
bea-2way-full

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text-classification

generated_from_trainer

deepset/gbert-base

text-embeddings-inference

endpoints_compatible

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bea-2way-full

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

Loss: 0.4846
N Samples: 827.0
Accuracy: 0.8452
Precision Macro: 0.8134
Recall Macro: 0.8163
F1 Macro: 0.8148
Qwk: 0.6297

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: 8
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: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	N Samples	Accuracy	Precision Macro	Recall Macro	F1 Macro	Qwk
0.5195	1.0	884	0.4426	827.0	0.7956	0.7553	0.7431	0.7485	0.4974
0.4061	2.0	1768	0.4384	827.0	0.8259	0.8085	0.7526	0.7717	0.5469
0.2922	3.0	2652	0.4846	827.0	0.8452	0.8134	0.8163	0.8148	0.6297

Framework versions

Transformers 5.1.0
Pytorch 2.10.0+cu128
Datasets 4.6.1
Tokenizers 0.22.2