fine-tuned-DatasetQAS-Squad-ID-with-indobert-large-p2-with-ITTL-with-freeze-LR-1e-05 – AI Model by muhammadravi251001 | AlphaNeural AI

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fine-tuned-DatasetQAS-Squad-ID-with-indobert-large-p2-with-ITTL-with-freeze-LR-1e-05

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fine-tuned-DatasetQAS-Squad-ID-with-indobert-large-p2-with-ITTL-with-freeze-LR-1e-05

This model is a fine-tuned version of indobenchmark/indobert-large-p2 on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.5574
Exact Match: 47.6371
F1: 63.8727

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: 1e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 128
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Exact Match	F1
1.8897	0.5	463	1.7933	39.8083	55.8203
1.6804	1.0	926	1.6326	44.1978	60.8018
1.5163	1.5	1389	1.5762	45.0303	60.8666
1.4687	2.0	1852	1.5214	46.6616	63.1627
1.3234	2.5	2315	1.5170	46.7793	63.1629
1.3221	3.0	2778	1.5037	47.2418	63.9784
1.1877	3.5	3241	1.5265	47.4773	63.7942
1.2091	4.0	3704	1.5262	47.3764	63.8722
1.0894	4.5	4167	1.5574	47.6371	63.8727

Framework versions

Transformers 4.26.1
Pytorch 1.13.1+cu117
Datasets 2.2.0
Tokenizers 0.13.2