llama_2_13b_Magiccoder_evol_10k_ortho_eye

This model is a fine-tuned version of meta-llama/Llama-2-13b-hf on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.0987

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: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 0.02
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss
1.2093	0.0262	4	1.2192
1.1816	0.0523	8	1.1667
1.1073	0.0785	12	1.1438
1.0563	0.1047	16	1.1321
1.0947	0.1308	20	1.1265
1.0662	0.1570	24	1.1237
1.0636	0.1832	28	1.1206
1.1163	0.2093	32	1.1180
1.0423	0.2355	36	1.1149
1.1226	0.2617	40	1.1148
1.0991	0.2878	44	1.1124
1.1427	0.3140	48	1.1119
1.1193	0.3401	52	1.1081
1.0908	0.3663	56	1.1086
1.1406	0.3925	60	1.1077
1.1366	0.4186	64	1.1063
1.0866	0.4448	68	1.1051
1.1035	0.4710	72	1.1026
1.0523	0.4971	76	1.1021
1.1381	0.5233	80	1.1018
1.1521	0.5495	84	1.1016
1.0932	0.5756	88	1.1014
1.0467	0.6018	92	1.0999
1.0459	0.6280	96	1.0992
1.1049	0.6541	100	1.0996
1.0905	0.6803	104	1.0993
1.0828	0.7065	108	1.0992
1.1141	0.7326	112	1.0990
1.0616	0.7588	116	1.0989
1.083	0.7850	120	1.0984
1.1081	0.8111	124	1.0982
1.069	0.8373	128	1.0984
1.0085	0.8635	132	1.0988
1.1178	0.8896	136	1.0987
1.0337	0.9158	140	1.0988
1.0825	0.9419	144	1.0987
1.0976	0.9681	148	1.0987
1.0909	0.9943	152	1.0987

Framework versions

• PEFT 0.7.1
• Transformers 4.40.2
• Pytorch 2.3.0+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1