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Dhanang/story_model

sourceHugging Facemitupdated 3y agoView on Hugging Face

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story_model

This model is a fine-tuned version of indobenchmark/indobert-base-p2 on an unknown dataset. It achieves the following results on the evaluation set:

—Loss: 0.2923
—Accuracy: 0.9409
—F1: 0.9043
—Precision: 0.9087
—Recall: 0.9

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
—trainbatchsize: 16
—evalbatchsize: 16
—seed: 42
—optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
—lrschedulertype: linear
—num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
No log	0.53	50	0.5324	0.8978	0.8032	0.9009	0.7572
No log	1.06	100	0.2795	0.9355	0.8967	0.8967	0.8967
No log	1.6	150	0.2561	0.9194	0.8772	0.8608	0.8972
No log	2.13	200	0.3274	0.9194	0.8635	0.8871	0.8444
No log	2.66	250	0.2756	0.9247	0.8819	0.8745	0.89
No log	3.19	300	0.4554	0.9032	0.8302	0.8696	0.8028
No log	3.72	350	0.2333	0.9462	0.9157	0.9075	0.9244
No log	4.26	400	0.4101	0.9247	0.8711	0.9013	0.8478
No log	4.79	450	0.2826	0.9409	0.9063	0.9021	0.9106

Framework versions

—Transformers 4.35.2
—Pytorch 2.1.0+cu121
—Datasets 2.15.0
—Tokenizers 0.15.0