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results – AI Model by Tohrumi | AlphaNeural AI
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safetensors
roberta
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vinai/phobert-base-v2
finetune
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This model is a fine-tuned version of
vinai/phobert-base-v2
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.7387
Accuracy: 0.69
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: 5e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.917
1.0
125
0.8013
0.642
0.7517
2.0
250
0.7507
0.669
0.6474
3.0
375
0.7387
0.69
Framework versions
Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.21.0
Tokenizers 0.19.1
