HAL_CafeBERT_finetuned – AI Model by Kuongan | AlphaNeural AI

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Kuongan/
HAL_CafeBERT_finetuned

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text-classification

generated_from_trainer

uitnlp/CafeBERT

text-embeddings-inference

endpoints_compatible

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HAL_CafeBERT_finetuned

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

Loss: 0.6655
Accuracy: 0.7786
F1 Macro: 0.7797

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: 28
eval_batch_size: 28
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: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Macro
No log	1.0	200	0.7259	0.7171	0.7206
No log	2.0	400	0.6178	0.7764	0.7766
0.7577	3.0	600	0.6655	0.7786	0.7797
0.7577	4.0	800	0.7700	0.7593	0.7602
0.3456	5.0	1000	1.0266	0.7421	0.7437
0.3456	6.0	1200	1.0115	0.7529	0.7537

Framework versions

Transformers 4.56.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.0