code-bench-CodeGemma-7B-cg-nv9n

Zacktree/code-bench-CodeGemma-7B-cg-nv9n

code-bench-CodeGemma-7B-cg-nv9n is a machine learning model from Zacktree. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as gemma.

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

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Repo size

64 GB

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Hugging Face

Repo makeup

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.safetensors1.6 GB · 99%

At a glance

Library: peft
License: gemma
Access: Public
Created: Sep 18, 2025
Updated: Sep 19, 2025
SHA: 366299e7

Base models

google/codegemma-7b

Model card

From the Hugging Face model README

code-bench-CodeGemma-7B-cg-nv9n

This model is a fine-tuned version of google/codegemma-7b on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0558

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: 1
eval_batch_size: 3
seed: 42
distributed_type: multi-GPU
gradient_accumulation_steps: 8
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.03
num_epochs: 4
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
0.623	0.0530	50	0.5961
0.473	0.1061	100	0.4669
0.4018	0.1591	150	0.3573
0.3249	0.2121	200	0.2696
0.2703	0.2652	250	0.2265
0.2066	0.3182	300	0.1859
0.1725	0.3713	350	0.1526
0.1588	0.4243	400	0.1341
0.1467	0.4773	450	0.1278
0.1349	0.5304	500	0.1229
0.1541	0.5834	550	0.1170
0.1262	0.6364	600	0.1137
0.1273	0.6895	650	0.1118
0.1322	0.7425	700	0.1091
0.1244	0.7955	750	0.1069
0.1134	0.8486	800	0.1043
0.1206	0.9016	850	0.1030
0.117	0.9547	900	0.1016
0.101	1.0077	950	0.1003
0.1095	1.0607	1000	0.0999
0.0989	1.1138	1050	0.0991
0.1054	1.1668	1100	0.0972
0.1073	1.2198	1150	0.0964
0.1057	1.2729	1200	0.0951
0.111	1.3259	1250	0.0953
0.0946	1.3789	1300	0.0935
0.0907	1.4320	1350	0.0926
0.0989	1.4850	1400	0.0919
0.1037	1.5381	1450	0.0905
0.0955	1.5911	1500	0.0899
0.0893	1.6441	1550	0.0887
0.1015	1.6972	1600	0.0881
0.0952	1.7502	1650	0.0874
0.0918	1.8032	1700	0.0868
0.0926	1.8563	1750	0.0860
0.0886	1.9093	1800	0.0852
0.0989	1.9623	1850	0.0841
0.0863	2.0154	1900	0.0839
0.0821	2.0684	1950	0.0836
0.0964	2.1215	2000	0.0830
0.0755	2.1745	2050	0.0824
0.0777	2.2275	2100	0.0817
0.0761	2.2806	2150	0.0807
0.0777	2.3336	2200	0.0802
0.0857	2.3866	2250	0.0795
0.0883	2.4397	2300	0.0793
0.0784	2.4927	2350	0.0785
0.0774	2.5457	2400	0.0779
0.0776	2.5988	2450	0.0772
0.0788	2.6518	2500	0.0770
0.0853	2.7064	2550	0.0768
0.0836	2.7595	2600	0.0764
0.0822	2.8125	2650	0.0758
0.0862	2.8656	2700	0.0755
0.0753	2.9186	2750	0.0750
0.0798	2.9716	2800	0.0744
0.0762	3.0247	2850	0.0741
0.0884	3.0777	2900	0.0736
0.0753	3.1307	2950	0.0731
0.0774	3.1838	3000	0.0727
0.0753	3.2368	3050	0.0725
0.0853	3.2898	3100	0.0723
0.0723	3.3429	3150	0.0718
0.0762	3.3959	3200	0.0713
0.0737	3.4490	3250	0.0712
0.0751	3.5020	3300	0.0705
0.0737	3.5550	3350	0.0700
0.069	3.6081	3400	0.0701
0.0696	3.6611	3450	0.0697
0.0725	3.7141	3500	0.0692
0.074	3.7672	3550	0.0686
0.0655	3.8202	3600	0.0684
0.0671	3.8732	3650	0.0679
0.0642	3.9263	3700	0.0676
0.0676	3.9801	3750	0.0670
0.0756	4.0331	3800	0.0669
0.0691	4.0862	3850	0.0667
0.0699	4.1392	3900	0.0659
0.0633	4.1923	3950	0.0658
0.0673	4.2453	4000	0.0655
0.0656	4.2983	4050	0.0653
0.0595	4.3514	4100	0.0648
0.0685	4.4044	4150	0.0644
0.0635	4.4574	4200	0.0641
0.0742	4.5105	4250	0.0637
0.0617	4.5635	4300	0.0634
0.0628	4.6165	4350	0.0629
0.0635	4.6696	4400	0.0629
0.0595	4.7226	4450	0.0623
0.0621	4.7757	4500	0.0624
0.0635	4.8287	4550	0.0621
0.0671	4.8817	4600	0.0615
0.0618	4.9348	4650	0.0613
0.0623	4.9878	4700	0.0606
0.057	5.0408	4750	0.0609
0.0529	5.0939	4800	0.0603
0.0582	5.1469	4850	0.0607
0.0577	5.1999	4900	0.0599
0.0561	5.2530	4950	0.0600
0.0591	5.3060	5000	0.0592
0.054	5.3591	5050	0.0596
0.0628	5.4121	5100	0.0590
0.0545	5.4651	5150	0.0586
0.0545	5.5182	5200	0.0582
0.0527	5.5712	5250	0.0581
0.0522	5.6242	5300	0.0581
0.0525	5.6773	5350	0.0575
0.0535	5.7303	5400	0.0574
0.0541	5.7833	5450	0.0579
0.0482	5.8364	5500	0.0566
0.0506	5.8894	5550	0.0562
0.0572	5.9425	5600	0.0558
0.0497	5.9955	5650	0.0558

Framework versions

PEFT 0.12.0
Transformers 4.44.2
Pytorch 2.5.1+cu121
Datasets 2.21.0
Tokenizers 0.19.1

Library: peft
License: gemma
Created: Sep 18, 2025
Updated: Sep 19, 2025