bea-2way-full-5ep – AI Model by khaled44 | AlphaNeural AI

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khaled44/
bea-2way-full-5ep

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text-classification

generated_from_trainer

deepset/gbert-base

text-embeddings-inference

endpoints_compatible

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bea-2way-full-5ep

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: 0.7300
N Samples: 827.0
Accuracy: 0.8356
Precision Macro: 0.8032
Recall Macro: 0.7988
F1 Macro: 0.8009
Qwk: 0.6018

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: 5.0

Training results

Training Loss	Epoch	Step	Validation Loss	N Samples	Accuracy	Precision Macro	Recall Macro	F1 Macro	Qwk
0.5248	1.0	884	0.4351	827.0	0.7932	0.7517	0.7449	0.7481	0.4963
0.4179	2.0	1768	0.4364	827.0	0.8247	0.8154	0.7422	0.7645	0.5347
0.3229	3.0	2652	0.5448	827.0	0.8259	0.7904	0.7931	0.7917	0.5834
0.2669	4.0	3536	0.6481	827.0	0.8283	0.7925	0.8043	0.7978	0.5959
0.1987	5.0	4420	0.7300	827.0	0.8356	0.8032	0.7988	0.8009	0.6018

Framework versions

Transformers 5.1.0
Pytorch 2.10.0+cu128
Datasets 4.6.1
Tokenizers 0.22.2