This model is a fine-tuned version of google/gemma-7b on the HuggingFaceH4/deita-10k-v0-sft dataset. It achieves the following results on the evaluation set:

Loss: 1.1043

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: 2e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 4
total_train_batch_size: 128
total_eval_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
1.5388	0.0835	25	1.5511
1.0986	0.1669	50	1.1441
1.0678	0.2504	75	1.0955
1.0528	0.3339	100	1.0925
1.0934	0.4174	125	1.1267
1.0648	0.5008	150	1.1338
1.0634	0.5843	175	1.1430
1.0406	0.6678	200	1.1117
1.0121	0.7513	225	1.0639
0.9433	0.8347	250	1.0389
0.9858	0.9182	275	1.0390
0.9786	1.0017	300	1.0929
0.7899	1.0851	325	1.1224
0.7882	1.1686	350	1.0742
0.7399	1.2521	375	1.0683
0.7628	1.3356	400	1.0628
0.7569	1.4190	425	1.0546
0.7535	1.5025	450	1.0615
0.7363	1.5860	475	1.0576
0.7552	1.6694	500	1.0607
0.7437	1.7529	525	1.0607
0.7519	1.8364	550	1.0658
0.7625	1.9199	575	1.0657
0.6916	2.0033	600	1.0868
0.4481	2.0868	625	1.1412
0.4438	2.1703	650	1.1363
0.4339	2.2538	675	1.1245
0.4356	2.3372	700	1.1193
0.4268	2.4207	725	1.1166
0.4259	2.5042	750	1.1127
0.4069	2.5876	775	1.1079
0.4018	2.6711	800	1.1046
0.4181	2.7546	825	1.1036
0.4007	2.8381	850	1.1050
0.3953	2.9215	875	1.1041

Framework versions

Transformers 4.45.2
Pytorch 2.5.1+rocm6.2
Datasets 3.2.0
Tokenizers 0.20.3

li-muyang/zephyr-7b-gemma-sft

zephyr-7b-gemma-sft

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

li-muyang/
zephyr-7b-gemma-sft