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RoBERTa_Tagalog_Symptom2Disease – AI Model by notlath | AlphaNeural AI | AlphaNeural AI
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notlath
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RoBERTa_Tagalog_Symptom2Disease
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transformers
safetensors
roberta
text-classification
generated_from_trainer
jcblaise/roberta-tagalog-base
finetune
cc-by-sa-4.0
text-embeddings-inference
endpoints_compatible
us
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final_filipino_model_retrained
This model is a fine-tuned version of
jcblaise/roberta-tagalog-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.3502
Accuracy: 0.9545
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: 3.687284551433047e-05
train_batch_size: 32
eval_batch_size: 32
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: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 8
label_smoothing_factor: 0.05
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.9281
1.0
34
0.4398
0.9091
0.2285
2.0
68
0.3403
0.9773
0.2039
3.0
102
0.3200
0.9773
0.2027
4.0
136
0.3164
0.9773
0.2024
5.0
170
0.3137
0.9773
Framework versions
Transformers 4.56.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.0
