phobert-large_baseline_syllables – AI Model by VampeeHuntee | AlphaNeural AI

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VampeeHuntee/
phobert-large_baseline_syllables

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token-classification

generated_from_trainer

vinai/phobert-large

autotrain_compatible

endpoints_compatible

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phobert-large_baseline_syllables

This model is a fine-tuned version of vinai/phobert-large on the covid19_ner dataset. It achieves the following results on the evaluation set:

Loss: 0.0933
Patient Id: 0.9859
Name: 0.9437
Gender: 0.9624
Age: 0.9656
Job: 0.7954
Location: 0.9517
Organization: 0.9037
Date: 0.9874
Symptom And Disease: 0.8808
Transportation: 0.9886
F1 Macro: 0.9365
F1 Micro: 0.9505

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Patient Id	Name	Gender	Age	Job	Location	Organization	Date	Symptom And Disease	Transportation	F1 Macro	F1 Micro
0.2696	1.0	629	0.1036	0.9758	0.9365	0.8730	0.8965	0.6113	0.9386	0.8447	0.9870	0.8494	0.9721	0.8885	0.9247
0.0518	2.0	1258	0.0801	0.9851	0.9491	0.9540	0.9709	0.6063	0.9393	0.8843	0.9887	0.8856	0.9503	0.9114	0.9416
0.0301	3.0	1887	0.0856	0.9867	0.9437	0.9524	0.9669	0.7812	0.9496	0.8909	0.9878	0.8740	0.9831	0.9316	0.9475
0.0213	4.0	2516	0.0923	0.9855	0.9465	0.9626	0.9605	0.7907	0.9495	0.8948	0.9874	0.8815	0.9775	0.9337	0.9486
0.0146	5.0	3145	0.0933	0.9859	0.9437	0.9624	0.9656	0.7954	0.9517	0.9037	0.9874	0.8808	0.9886	0.9365	0.9505

Framework versions

Transformers 4.41.2
Pytorch 2.1.2
Datasets 2.19.2
Tokenizers 0.19.1