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

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fine-tuned-DatasetQAS-Squad-ID-with-indobert-base-uncased-without-ITTL-without-freeze-LR-1e-05

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fine-tuned-DatasetQAS-Squad-ID-with-indobert-base-uncased-without-ITTL-without-freeze-LR-1e-05

This model is a fine-tuned version of indolem/indobert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.5081
Exact Match: 48.0441
F1: 64.5121

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: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
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
2.0164	0.5	463	1.8536	39.4212	54.9381
1.8356	1.0	926	1.6789	43.3667	59.1353
1.6492	1.5	1389	1.6111	45.0324	61.1553
1.6051	2.0	1852	1.5722	45.5119	62.1336
1.4925	2.5	2315	1.5679	46.5130	63.6738
1.5049	3.0	2778	1.5260	47.2197	64.2953
1.3868	3.5	3241	1.5213	47.6571	64.6843
1.3574	4.0	3704	1.5065	47.8758	64.3476
1.3199	4.5	4167	1.5169	47.6403	64.4273
1.3024	5.0	4630	1.5081	48.0441	64.5121

Framework versions

Transformers 4.27.4
Pytorch 1.13.1+cu117
Datasets 2.2.0
Tokenizers 0.13.2