afaji/fine-tuned-DatasetQAS-TYDI-QA-ID-with-indobert-large-p2-without-ITTL-without-freeze-LR-1e-05

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

fine-tuned-DatasetQAS-TYDI-QA-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: 1.3674
• —Exact Match: 61.6056
• —F1: 75.5602
• —Precision: 77.4368
• —Recall: 81.6689

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
• —trainbatchsize: 16
• —evalbatchsize: 16
• —seed: 42
• —gradientaccumulationsteps: 4
• —totaltrainbatch_size: 64
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 16

Training results

Framework versions

• —Transformers 4.27.0
• —Pytorch 2.0.0+cu117
• —Datasets 2.2.0
• —Tokenizers 0.13.2