gemma2_on_korean_summary

This model is a fine-tuned version of beomi/gemma-ko-2b on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.9622

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: 2
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 5
• total_train_batch_size: 10
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 50
• training_steps: 800
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
1.6606	0.26	20	1.5454
1.4381	0.53	40	1.3247
1.2548	0.79	60	1.1921
1.1574	1.05	80	1.1227
1.0968	1.32	100	1.0727
1.0485	1.58	120	1.0316
1.0258	1.84	140	1.0019
0.9582	2.11	160	0.9785
0.906	2.37	180	0.9575
0.8837	2.63	200	0.9429
0.8763	2.89	220	0.9247
0.8295	3.16	240	0.9213
0.7799	3.42	260	0.9122
0.7742	3.68	280	0.8992
0.7708	3.95	300	0.8918
0.7196	4.21	320	0.8952
0.6908	4.47	340	0.8917
0.6977	4.74	360	0.8841
0.6789	5.0	380	0.8764
0.6198	5.26	400	0.9003
0.6203	5.53	420	0.9030
0.6169	5.79	440	0.8913
0.6111	6.05	460	0.8935
0.564	6.32	480	0.9096
0.5819	6.58	500	0.9027
0.5673	6.84	520	0.8997
0.5382	7.11	540	0.9181
0.5228	7.37	560	0.9197
0.5197	7.63	580	0.9254
0.5319	7.89	600	0.9158
0.4954	8.16	620	0.9394
0.4954	8.42	640	0.9345
0.4719	8.68	660	0.9388
0.4866	8.95	680	0.9390
0.4739	9.21	700	0.9528
0.4591	9.47	720	0.9534
0.4478	9.74	740	0.9542
0.4547	10.0	760	0.9539
0.4379	10.26	780	0.9617
0.4348	10.53	800	0.9622

Framework versions

• PEFT 0.8.2
• Transformers 4.38.2
• Pytorch 2.1.2+cu121
• Datasets 2.17.0
• Tokenizers 0.15.0