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jafarabdurrohman/
indonesian-roberta-base-ler

Name: indonesian-roberta-base-ler
Availability: InStock

generated_from_trainer

mit

autotrain_compatible

endpoints_compatible

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indonesian-roberta-base-ler

This model is a fine-tuned version of flax-community/indonesian-roberta-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0291
Overall Precision: 0.9294
Overall Recall: 0.9191
Overall F1: 0.9242
Overall Accuracy: 0.9968
Jenis amar F1: 0.9379
Jenis dakwaan F1: 0.8644
Jenis perkara F1: 0.9096
Melanggar uu (dakwaan) F1: 0.8062
Melanggar uu (pertimbangan hukum) F1: 0.6441
Melanggar uu (tuntutan) F1: 0.9248
Nama hakim anggota F1: 0.9640
Nama hakim ketua F1: 0.9741
Nama jaksa F1: 0.9614
Nama panitera F1: 0.9756
Nama pengacara F1: 0.9000
Nama pengadilan F1: 0.9982
Nama saksi F1: 0.9386
Nama terdakwa F1: 0.9786
Nomor putusan F1: 0.9963
Putusan hukuman F1: 0.9433
Tanggal kejadian F1: 0.3988
Tanggal putusan F1: 0.9680
Tingkat kasus F1: 0.9853
Tuntutan hukuman F1: 0.8867

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
max_sequence_length: 128
stride: 0%
decay_rate: 0.01
num_epochs: 16

Training results

Training Loss	Epoch	Step	Validation Loss	Overall Precision	Overall Recall	Overall F1	Overall Accuracy	Jenis amar F1	Jenis dakwaan F1	Jenis perkara F1	Melanggar uu (dakwaan) F1	Melanggar uu (pertimbangan hukum) F1	Melanggar uu (tuntutan) F1	Nama hakim anggota F1	Nama hakim ketua F1	Nama jaksa F1	Nama panitera F1	Nama pengacara F1	Nama pengadilan F1	Nama saksi F1	Nama terdakwa F1	Nomor putusan F1	Putusan hukuman F1	Tanggal kejadian F1	Tanggal putusan F1	Tingkat kasus F1	Tuntutan hukuman F1
0.0204	1.0	5641	0.0163	0.8647	0.8564	0.8605	0.9960	0.8723	0.5028	0.7307	0.6945	0.5383	0.8472	0.9192	0.9389	0.9086	0.9449	0.7881	0.9821	0.8989	0.9423	0.9530	0.7655	0.3135	0.9630	0.9575	0.7803
0.0133	2.0	11282	0.0193	0.8305	0.8274	0.8289	0.9945	0.8316	0.6958	0.6978	0.6186	0.3940	0.8116	0.8620	0.8495	0.8338	0.8849	0.5220	0.9690	0.9036	0.9532	0.9927	0.1196	0.3154	0.9290	0.8864	0.6835
0.0099	3.0	16923	0.0163	0.8455	0.8801	0.8624	0.9960	0.9	0.7671	0.7539	0.5686	0.4050	0.4949	0.9267	0.9168	0.9281	0.9353	0.7831	0.9910	0.8946	0.9722	0.9895	0.8827	0.3423	0.9474	0.9610	0.8459
0.0079	4.0	22564	0.0164	0.8627	0.9019	0.8819	0.9958	0.9022	0.7602	0.7336	0.7157	0.5674	0.8599	0.9550	0.9515	0.9631	0.9695	0.8184	0.9679	0.9131	0.9780	0.9963	0.8650	0.3234	0.9564	0.9722	0.8262
0.0059	5.0	28205	0.0179	0.9157	0.8947	0.9050	0.9968	0.9017	0.7932	0.8425	0.7648	0.5989	0.8992	0.9531	0.9373	0.9560	0.9660	0.8232	0.9784	0.9136	0.9642	0.9898	0.9051	0.3933	0.9645	0.9630	0.8470
0.0052	6.0	33846	0.0183	0.8523	0.8960	0.8736	0.9960	0.8923	0.8015	0.8443	0.7440	0.5949	0.8528	0.9339	0.8898	0.9348	0.9620	0.8814	1.0	0.9156	0.9613	0.9936	0.8604	0.2037	0.8600	0.9646	0.8483
0.005	7.0	39487	0.0183	0.8901	0.9073	0.8986	0.9965	0.9150	0.7942	0.8355	0.7872	0.6258	0.8641	0.9514	0.9573	0.9665	0.9676	0.8746	0.9964	0.9223	0.9680	0.9945	0.8970	0.3249	0.9354	0.9759	0.8407
0.0039	8.0	45128	0.0197	0.8915	0.9016	0.8965	0.9962	0.9125	0.7638	0.7435	0.7406	0.5828	0.8394	0.9562	0.9683	0.9456	0.9702	0.7469	1.0	0.8969	0.9595	0.9969	0.9067	0.3916	0.9404	0.9722	0.8621
0.0031	9.0	50769	0.0225	0.8661	0.9179	0.8913	0.9959	0.9306	0.7714	0.7939	0.7900	0.6084	0.9049	0.9591	0.9643	0.9457	0.9527	0.8127	0.9964	0.9080	0.9716	0.9970	0.9064	0.3388	0.8412	0.9593	0.8727
0.0022	10.0	56410	0.0232	0.9254	0.9111	0.9182	0.9967	0.9212	0.8411	0.9080	0.8044	0.6126	0.9243	0.9560	0.9741	0.9591	0.9642	0.9102	0.9874	0.9240	0.9734	0.9941	0.9351	0.4186	0.9626	0.9779	0.8687
0.0023	11.0	62051	0.0209	0.9289	0.9114	0.9201	0.9969	0.9297	0.8423	0.8843	0.7986	0.6318	0.8808	0.9645	0.9624	0.9585	0.9674	0.8963	0.9946	0.9309	0.9752	0.9966	0.9320	0.4092	0.9697	0.9871	0.8790
0.001	12.0	67692	0.0230	0.9279	0.9075	0.9176	0.9968	0.9377	0.8665	0.8771	0.7951	0.6213	0.9079	0.9611	0.9768	0.9576	0.9638	0.9174	0.9964	0.9353	0.9621	0.9967	0.9391	0.3735	0.9665	0.9703	0.8666
0.0007	13.0	73333	0.0244	0.9095	0.9190	0.9142	0.9965	0.9400	0.8610	0.8974	0.8030	0.6337	0.9338	0.9660	0.9712	0.9565	0.9668	0.9181	0.9964	0.9273	0.9640	0.9961	0.9233	0.3664	0.9697	0.9668	0.8845
0.0006	14.0	78974	0.0258	0.9213	0.9186	0.9200	0.9967	0.9315	0.8533	0.9119	0.7934	0.6453	0.9311	0.9617	0.9749	0.9614	0.9702	0.8718	0.9910	0.9320	0.9726	0.9966	0.9249	0.3936	0.9680	0.9871	0.8728
0.0003	15.0	84615	0.0281	0.9260	0.9208	0.9234	0.9969	0.9313	0.8463	0.9150	0.7996	0.6601	0.9176	0.9677	0.9712	0.9599	0.9749	0.8928	0.9946	0.9351	0.9793	0.9963	0.9347	0.3956	0.9680	0.9852	0.8854
0.0001	16.0	90256	0.0291	0.9294	0.9191	0.9242	0.9968	0.9379	0.8644	0.9096	0.8062	0.6441	0.9248	0.9640	0.9741	0.9614	0.9756	0.9000	0.9982	0.9386	0.9786	0.9963	0.9433	0.3988	0.9680	0.9853	0.8867

Framework versions

Transformers 4.28.1
Pytorch 2.0.1
Datasets 2.12.0
Tokenizers 0.13.3

jafarabdurrohman/indonesian-roberta-base-ler

indonesian-roberta-base-ler

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jafarabdurrohman/
indonesian-roberta-base-ler