indobert-base-p2-finetuned-mer-80k – AI Model by stevenwh | AlphaNeural AI

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stevenwh/
indobert-base-p2-finetuned-mer-80k

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indobert-base-p2-finetuned-mer-80k

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

Loss: 1.4680

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: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
2.9647	1.0	2305	2.1419
2.0987	2.0	4610	1.8580
1.8866	3.0	6915	1.7170
1.7696	4.0	9220	1.6357
1.6951	5.0	11525	1.5761
1.6383	6.0	13830	1.5354
1.599	7.0	16135	1.5074
1.5738	8.0	18440	1.4862
1.5516	9.0	20745	1.4700
1.5382	10.0	23050	1.4633

Framework versions

Transformers 4.24.0
Pytorch 1.13.0
Datasets 2.7.0
Tokenizers 0.13.2