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phobert_llm_results – AI Model by BonTori | AlphaNeural AI
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phobert_llm_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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phobert_llm_results
This model is a fine-tuned version of
vinai/phobert-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.4929
Accuracy: 0.8306
F1: 0.5973
Precision: 0.6064
Recall: 0.6092
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
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
Precision
Recall
0.5029
1.0
5518
0.4589
0.8287
0.5859
0.6119
0.5799
0.3703
2.0
11036
0.4578
0.8294
0.5981
0.6135
0.5943
0.2995
3.0
16554
0.5023
0.8283
0.6041
0.6050
0.6093
Framework versions
Transformers 5.13.1
Pytorch 2.11.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
