indonesian-wiki-lang-adapter

DGurgurov/indonesian-wiki-lang-adapter

indonesian-wiki-lang-adapter is a machine learning model from DGurgurov. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.

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

Downloads · 30 days

Access

Public

Updated Mar 2, 2024

Repo size

386 MB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin374 MB · 96%

At a glance

License: apache-2.0
Access: Public
Created: Mar 1, 2024
Updated: Mar 2, 2024
SHA: 12b6ea16

Base models

Model card

From the Hugging Face model README

ms

This model is a fine-tuned version of bert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.4335
Accuracy: 0.7183

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: 5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
distributed_type: multi-GPU
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
training_steps: 50000

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.8607	0.05	500	1.6380	0.6876
1.7966	0.1	1000	1.6063	0.6916
1.7581	0.15	1500	1.5902	0.6949
1.7313	0.2	2000	1.5726	0.6975
1.7143	0.25	2500	1.5630	0.6992
1.7074	0.3	3000	1.5562	0.6997
1.699	0.34	3500	1.5440	0.7020
1.6797	0.39	4000	1.5376	0.7026
1.6813	0.44	4500	1.5355	0.7028
1.6641	0.49	5000	1.5276	0.7041
1.672	0.54	5500	1.5212	0.7048
1.6506	0.59	6000	1.5167	0.7058
1.6592	0.64	6500	1.5083	0.7069
1.6386	0.69	7000	1.5050	0.7071
1.6449	0.74	7500	1.5033	0.7078
1.6362	0.79	8000	1.5032	0.7073
1.6337	0.84	8500	1.4978	0.7082
1.622	0.89	9000	1.4971	0.7089
1.6279	0.94	9500	1.4919	0.7094
1.6199	0.98	10000	1.4900	0.7096
1.6218	1.03	10500	1.4914	0.7099
1.6144	1.08	11000	1.4814	0.7113
1.6017	1.13	11500	1.4789	0.7113
1.6092	1.18	12000	1.4755	0.7119
1.6083	1.23	12500	1.4766	0.7119
1.6081	1.28	13000	1.4791	0.7113
1.615	1.33	13500	1.4722	0.7127
1.605	1.38	14000	1.4725	0.7124
1.598	1.43	14500	1.4763	0.7119
1.6004	1.48	15000	1.4661	0.7132
1.6074	1.53	15500	1.4713	0.7123
1.603	1.58	16000	1.4658	0.7135
1.5928	1.62	16500	1.4646	0.7135
1.5942	1.67	17000	1.4676	0.7132
1.5914	1.72	17500	1.4604	0.7145
1.5931	1.77	18000	1.4580	0.7142
1.5808	1.82	18500	1.4606	0.7148
1.5911	1.87	19000	1.4592	0.7143
1.5842	1.92	19500	1.4622	0.7143
1.5838	1.97	20000	1.4584	0.7146
1.585	2.02	20500	1.4630	0.7139
1.5772	2.07	21000	1.4557	0.7146
1.589	2.12	21500	1.4556	0.7151
1.5653	2.17	22000	1.4533	0.7154
1.5753	2.22	22500	1.4574	0.7152
1.5707	2.26	23000	1.4531	0.7155
1.5744	2.31	23500	1.4534	0.7153
1.5741	2.36	24000	1.4531	0.7155
1.5696	2.41	24500	1.4480	0.7161
1.5844	2.46	25000	1.4526	0.7157
1.576	2.51	25500	1.4478	0.7160
1.5621	2.56	26000	1.4497	0.7158
1.5707	2.61	26500	1.4514	0.7159
1.5819	2.66	27000	1.4478	0.7164
1.5663	2.71	27500	1.4503	0.7159
1.5834	2.76	28000	1.4507	0.7160
1.5726	2.81	28500	1.4426	0.7165
1.5695	2.86	29000	1.4466	0.7166
1.5791	2.9	29500	1.4464	0.7167
1.5711	2.95	30000	1.4434	0.7170
1.5724	3.0	30500	1.4423	0.7169
1.5648	3.05	31000	1.4410	0.7173
1.5666	3.1	31500	1.4427	0.7168
1.567	3.15	32000	1.4424	0.7170
1.5569	3.2	32500	1.4441	0.7168
1.5717	3.25	33000	1.4385	0.7182
1.5585	3.3	33500	1.4416	0.7175
1.5572	3.35	34000	1.4415	0.7174
1.5585	3.4	34500	1.4368	0.7181
1.5705	3.45	35000	1.4400	0.7178
1.5712	3.5	35500	1.4420	0.7173
1.5651	3.55	36000	1.4355	0.7186
1.5595	3.59	36500	1.4363	0.7179
1.5613	3.64	37000	1.4385	0.7179
1.5594	3.69	37500	1.4422	0.7172
1.5574	3.74	38000	1.4370	0.7179
1.5557	3.79	38500	1.4410	0.7177
1.5649	3.84	39000	1.4349	0.7181
1.5635	3.89	39500	1.4406	0.7174
1.5569	3.94	40000	1.4362	0.7182
1.5661	3.99	40500	1.4369	0.7180
1.5612	4.04	41000	1.4380	0.7178
1.5632	4.09	41500	1.4374	0.7180
1.5617	4.14	42000	1.4374	0.7178
1.5452	4.19	42500	1.4341	0.7185
1.5644	4.23	43000	1.4358	0.7181
1.5448	4.28	43500	1.4392	0.7178
1.559	4.33	44000	1.4363	0.7180
1.5599	4.38	44500	1.4332	0.7185
1.5586	4.43	45000	1.4391	0.7179
1.5527	4.48	45500	1.4355	0.7183
1.5592	4.53	46000	1.4314	0.7187
1.55	4.58	46500	1.4352	0.7179
1.5592	4.63	47000	1.4367	0.7180
1.5586	4.68	47500	1.4346	0.7183
1.5547	4.73	48000	1.4321	0.7192
1.5572	4.78	48500	1.4397	0.7174
1.5537	4.83	49000	1.4334	0.7186
1.5546	4.87	49500	1.4347	0.7181
1.5518	4.92	50000	1.4365	0.7183

Framework versions

Transformers 4.36.2
Pytorch 2.0.0
Datasets 2.15.0
Tokenizers 0.15.0

License: apache-2.0
Created: Mar 1, 2024
Updated: Mar 2, 2024