Hal_phobert-large_finetuned – AI Model by Kuongan | AlphaNeural AI

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Kuongan/
Hal_phobert-large_finetuned

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text-classification

generated_from_trainer

vinai/phobert-large

endpoints_compatible

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Hal_phobert-large_finetuned

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

Loss: 0.7847
Accuracy: 0.7407
F1 Macro: 0.7417

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: 64
eval_batch_size: 64
seed: 42
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: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Macro
1.0956	1.0	88	0.7993	0.6786	0.6786
0.7654	2.0	176	0.7491	0.71	0.7089
0.618	3.0	264	0.7432	0.7257	0.7287
0.4807	4.0	352	0.7847	0.7407	0.7417
0.3665	5.0	440	0.8301	0.7357	0.7376
0.2522	6.0	528	0.8437	0.735	0.7364
0.2095	7.0	616	0.9808	0.7357	0.7362

Framework versions

Transformers 4.52.4
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.2