fine-tuned-DatasetQAS-Squad-ID-with-indobert-large-p2-without-ITTL-without-freeze-LR-1e-05 – AI Model by muhammadravi251001 | AlphaNeural AI

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fine-tuned-DatasetQAS-Squad-ID-with-indobert-large-p2-without-ITTL-without-freeze-LR-1e-05

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fine-tuned-DatasetQAS-Squad-ID-with-indobert-large-p2-without-ITTL-without-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: 1.5397
Exact Match: 47.8725
F1: 64.1189

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 16
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
1.8628	0.5	463	1.7727	40.7249	56.9043
1.6706	1.0	926	1.6163	44.3912	61.0635
1.5058	1.5	1389	1.5655	45.4339	61.5089
1.4661	2.0	1852	1.5130	46.9055	63.5850
1.3171	2.5	2315	1.5077	47.1914	63.4762
1.3258	3.0	2778	1.4981	47.6034	64.3797
1.1835	3.5	3241	1.5171	47.7043	64.1444
1.1946	4.0	3704	1.5333	47.6539	64.3327
1.0904	4.5	4167	1.5397	47.8725	64.1189

Framework versions

Transformers 4.26.1
Pytorch 1.13.1+cu117
Datasets 2.2.0
Tokenizers 0.13.2