lm-002-2

intanm/lm-002-2

lm-002-2 is a fill-mask model from intanm. Use it when you need the model to fill a missing word. It is set up for transformers. The card lists the license as mit.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Fill-Mask
Library: transformers
License: mit
Model type: bert
Access: Public
Created: Mar 31, 2023
Updated: Mar 31, 2023
SHA: e51c7236

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Model card

From the Hugging Face model README

lm-002-2

This model is a fine-tuned version of indobenchmark/indobert-base-p1 on the None dataset. It achieves the following results on the evaluation set:

Loss: 2.2632

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: 8
eval_batch_size: 8
seed: 42
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
No log	1.0	445	3.3647
3.9335	2.0	890	2.8834
3.0816	3.0	1335	2.6931
2.789	4.0	1780	2.5205
2.5818	5.0	2225	2.4183
2.4639	6.0	2670	2.3894
2.3898	7.0	3115	2.3479
2.3209	8.0	3560	2.2665
2.2683	9.0	4005	2.2642
2.2683	10.0	4450	2.2418

Framework versions

Transformers 4.27.4
Pytorch 1.13.1+cu116
Datasets 2.11.0
Tokenizers 0.13.2

Task: Fill-Mask
Library: transformers
Type: bert
License: mit
Created: Mar 31, 2023
Updated: Mar 31, 2023