You can deploy this model and start earning money today!

DGurgurov/
indonesian-wiki-lang-adapter

Name: indonesian-wiki-lang-adapter
Availability: InStock

tensorboard

generated_from_trainer

google-bert/bert-base-multilingual-cased

finetune

apache-2.0

Views

No views yet

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

DGurgurov/indonesian-wiki-lang-adapter

ms

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

DGurgurov/
indonesian-wiki-lang-adapter