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results – AI Model by Binz113 | AlphaNeural AI
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Binz113
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results
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transformers
safetensors
roberta
text-classification
generated_from_trainer
vinai/phobert-base
finetune
mit
endpoints_compatible
us
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results
This model is a fine-tuned version of
vinai/phobert-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.3902
Accuracy: 0.8757
F1: 0.8703
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: 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: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
0.3763
1.0
1503
0.4285
0.8671
0.8431
0.3067
2.0
3006
0.3809
0.8720
0.8650
0.2454
3.0
4509
0.3902
0.8757
0.8703
Framework versions
Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
