data

This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the generator dataset. It achieves the following results on the evaluation set:

• Loss: 1.1832

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: 0.0002
• train_batch_size: 1
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 4
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 1
• training_steps: 1000

Training results

Training Loss	Epoch	Step	Validation Loss
0.9391	0.1479	25	0.6653
0.6138	0.2959	50	0.6126
0.6039	0.4438	75	0.6061
0.5927	0.5917	100	0.5998
0.5973	0.7396	125	0.5946
0.602	0.8876	150	0.5943
0.547	1.0355	175	0.6319
0.4239	1.1834	200	0.6169
0.4301	1.3314	225	0.6158
0.4176	1.4793	250	0.6193
0.4295	1.6272	275	0.6242
0.4252	1.7751	300	0.6265
0.4252	1.9231	325	0.6264
0.3591	2.0710	350	0.6893
0.2758	2.2189	375	0.7153
0.2702	2.3669	400	0.7170
0.2797	2.5148	425	0.7173
0.2727	2.6627	450	0.7144
0.2817	2.8107	475	0.7169
0.2798	2.9586	500	0.7016
0.1922	3.1065	525	0.8090
0.16	3.2544	550	0.8373
0.1623	3.4024	575	0.8372
0.1632	3.5503	600	0.8402
0.1618	3.6982	625	0.8558
0.1732	3.8462	650	0.8581
0.1687	3.9941	675	0.8611
0.0961	4.1420	700	0.9902
0.0879	4.2899	725	1.0102
0.0899	4.4379	750	1.0345
0.0899	4.5858	775	1.0256
0.0882	4.7337	800	1.0273
0.0893	4.8817	825	1.0559
0.0824	5.0296	850	1.0753
0.052	5.1775	875	1.1582
0.052	5.3254	900	1.1643
0.0526	5.4734	925	1.1923
0.0497	5.6213	950	1.1759
0.0496	5.7692	975	1.1812
0.0477	5.9172	1000	1.1832

Framework versions

• PEFT 0.10.0
• Transformers 4.40.0
• Pytorch 2.2.2
• Datasets 2.19.0
• Tokenizers 0.19.1