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phobert-base-finetuned – AI Model by PaulTran | AlphaNeural AI
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PaulTran
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phobert-base-finetuned
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transformers
tensorboard
safetensors
roberta
multiple-choice
generated_from_trainer
vinai/phobert-base
finetune
endpoints_compatible
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phobert-base-finetuned
This model is a fine-tuned version of
vinai/phobert-base
on an unknown dataset. It achieves the following results on the evaluation set:
eval_loss: 1.3863
eval_accuracy: 0.2459
eval_runtime: 93.3925
eval_samples_per_second: 60.797
eval_steps_per_second: 3.801
epoch: 7.0
step: 9940
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: 0.0027
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10
Framework versions
Transformers 4.35.0
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1
