opus-mt-en-id-opus100

This model was trained from scratch on the opus100 dataset. It achieves the following results on the evaluation set:

• Loss: 2.3682
• Bleu: 27.5354

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: 0.0001
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 4000
• num_epochs: 25

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu
1.6086	1.0	31250	1.7099	29.4293
1.5762	2.0	62500	1.7410	28.948
1.5027	3.0	93750	1.7678	28.6931
1.4377	4.0	125000	1.7798	28.9463
1.3763	5.0	156250	1.8019	28.4966
1.3198	6.0	187500	1.8202	29.6279
1.2648	7.0	218750	1.8312	29.8151
1.2115	8.0	250000	1.8490	29.3032
1.1584	9.0	281250	1.8729	28.7282
1.1067	10.0	312500	1.8971	29.4797
1.0555	11.0	343750	1.9405	29.3416
1.0052	12.0	375000	1.9554	29.0168
0.956	13.0	406250	2.0001	28.2454
0.9069	14.0	437500	2.0282	28.6705
0.8589	15.0	468750	2.0591	28.1988
0.8115	16.0	500000	2.0944	28.2227
0.765	17.0	531250	2.1294	28.4351
0.7203	18.0	562500	2.1680	27.9764
0.6769	19.0	593750	2.2013	28.2986
0.6349	20.0	625000	2.2339	27.165
0.5957	21.0	656250	2.2795	27.5845
0.5589	22.0	687500	2.3037	27.7201
0.5246	23.0	718750	2.3311	27.3305
0.4944	24.0	750000	2.3487	27.3965
0.469	25.0	781250	2.3682	27.5354

Framework versions

• Transformers 4.26.1
• Pytorch 2.0.0
• Datasets 2.10.1
• Tokenizers 0.11.0