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results – AI Model by Edelweisse | AlphaNeural AI
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Edelweisse
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results
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transformers
safetensors
bert
text-classification
generated_from_trainer
ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa
finetune
mit
autotrain_compatible
endpoints_compatible
us
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results
This model is a fine-tuned results on the evaluation set:
Loss: 0.4952
Accuracy: 0.8351
F1: 0.8359
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: 3e-05
train_batch_size: 16
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 200
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
0.6964
1.0
73
0.5906
0.8110
0.8152
0.6407
2.0
146
0.4614
0.8007
0.8035
0.418
3.0
219
0.4952
0.8351
0.8359
0.1811
4.0
292
0.5943
0.8110
0.8114
0.1383
5.0
365
0.6963
0.8110
0.8121
Framework versions
Transformers 4.41.1
Pytorch 2.3.0+cu118
Datasets 2.19.1
Tokenizers 0.19.1
