phobert-large_baseline_words – AI Model by VampeeHuntee | AlphaNeural AI

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VampeeHuntee/
phobert-large_baseline_words

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token-classification

generated_from_trainer

vinai/phobert-large

autotrain_compatible

endpoints_compatible

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phobert-large_baseline_words

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: 0.0943
Patient Id: 0.9863
Name: 0.9542
Gender: 0.9664
Age: 0.9633
Job: 0.8300
Location: 0.9521
Organization: 0.9188
Date: 0.9842
Symptom And Disease: 0.8773
Transportation: 1.0
F1 Macro: 0.9433
F1 Micro: 0.9521

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
0.2801	1.0	629	0.0981	0.9840	0.9455	0.9045	0.9010	0.5837	0.9265	0.8726	0.9812	0.8611	0.9831	0.8943	0.9266
0.0446	2.0	1258	0.0897	0.9863	0.9549	0.9501	0.9722	0.7833	0.9355	0.8907	0.9852	0.8814	0.9721	0.9312	0.9434
0.0283	3.0	1887	0.0809	0.9867	0.9516	0.9551	0.9695	0.7857	0.9487	0.9086	0.9860	0.8845	1.0	0.9376	0.9502
0.0198	4.0	2516	0.0905	0.9863	0.9542	0.9647	0.9633	0.8287	0.9483	0.9159	0.9842	0.8897	1.0	0.9435	0.9516
0.0134	5.0	3145	0.0943	0.9863	0.9542	0.9664	0.9633	0.8300	0.9521	0.9188	0.9842	0.8773	1.0	0.9433	0.9521

Framework versions

Transformers 4.41.2
Pytorch 2.1.2
Datasets 2.19.2
Tokenizers 0.19.1