ice_llama2

thorirhrafn/ice_llama2

ice_llama2 is a machine learning model from thorirhrafn. 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.

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

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Repo size

4.3 GB

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Hugging Face

Repo makeup

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.safetensors1.1 GB · 99%

At a glance

Library: peft
Access: Public
Created: Jan 24, 2024
Updated: Mar 1, 2024
SHA: 289bb582

Base models

meta-llama/Llama-2-7b-hf

Model card

From the Hugging Face model README

ice_llama2

This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 2.3080

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
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
2.6464	0.02	10000	2.5455
2.4927	0.03	20000	2.4736
2.5238	0.05	30000	2.4381
2.4711	0.07	40000	2.4124
2.4345	0.08	50000	2.3989
2.3715	0.1	60000	2.3878
2.4212	0.12	70000	2.3786
2.434	0.14	80000	2.3724
2.4798	0.15	90000	2.3670
2.4343	0.17	100000	2.3615
2.4365	0.19	110000	2.3571
2.398	0.2	120000	2.3538
2.4734	0.22	130000	2.3510
2.4356	0.24	140000	2.3499
2.4512	0.25	150000	2.3458
2.4331	0.27	160000	2.3438
2.3749	0.29	170000	2.3409
2.4375	0.3	180000	2.3397
2.3301	0.32	190000	2.3378
2.4341	0.34	200000	2.3364
2.3286	0.36	210000	2.3356
2.3173	0.37	220000	2.3332
2.4105	0.39	230000	2.3333
2.3553	0.41	240000	2.3311
2.386	0.42	250000	2.3307
2.3761	0.44	260000	2.3294
2.42	0.46	270000	2.3277
2.44	0.47	280000	2.3267
2.4169	0.49	290000	2.3276
2.3254	0.51	300000	2.3265
2.4326	0.52	310000	2.3252
2.4203	0.54	320000	2.3244
2.4401	0.56	330000	2.3242
2.4005	0.57	340000	2.3221
2.3734	0.59	350000	2.3223
2.331	0.61	360000	2.3223
2.4652	0.63	370000	2.3220
2.3741	0.64	380000	2.3211
2.3634	0.66	390000	2.3193
2.3688	0.68	400000	2.3201
2.3284	0.69	410000	2.3195
2.4486	0.71	420000	2.3184
2.4113	0.73	430000	2.3183
2.3442	0.74	440000	2.3175
2.3414	0.76	450000	2.3176
2.3534	0.78	460000	2.3166
2.3384	0.79	470000	2.3170
2.4021	0.81	480000	2.3163
2.2645	0.83	490000	2.3161
2.3392	0.85	500000	2.3158
2.3499	0.86	510000	2.3155
2.3111	0.88	520000	2.3149
2.3604	0.9	530000	2.3139
2.4264	0.91	540000	2.3144
2.4964	0.93	550000	2.3138
2.5121	0.95	560000	2.3129
2.3389	0.96	570000	2.3129
2.3755	0.98	580000	2.3131
2.414	1.0	590000	2.3129
2.2656	1.01	600000	2.3127
2.3372	1.03	610000	2.3120
2.3479	1.05	620000	2.3126
2.3752	1.07	630000	2.3121
2.3685	1.08	640000	2.3118
2.4521	1.1	650000	2.3117
2.426	1.12	660000	2.3113
2.4583	1.13	670000	2.3114
2.414	1.15	680000	2.3107
2.3833	1.17	690000	2.3107
2.3053	1.18	700000	2.3107
2.2819	1.2	710000	2.3108
2.4079	1.22	720000	2.3106
2.4529	1.23	730000	2.3101
2.3139	1.25	740000	2.3102
2.3249	1.27	750000	2.3104
2.3575	1.28	760000	2.3102
2.3568	1.3	770000	2.3102
2.3686	1.32	780000	2.3096
2.34	1.34	790000	2.3098
2.4017	1.35	800000	2.3096
2.4174	1.37	810000	2.3096
2.3793	1.39	820000	2.3092
2.4362	1.4	830000	2.3094
2.4015	1.42	840000	2.3091
2.4451	1.44	850000	2.3089
2.369	1.45	860000	2.3091
2.408	1.47	870000	2.3091
2.4213	1.49	880000	2.3088
2.4088	1.5	890000	2.3090
2.3602	1.52	900000	2.3090
2.3525	1.54	910000	2.3087
2.421	1.56	920000	2.3086
2.4586	1.57	930000	2.3083
2.4173	1.59	940000	2.3084
2.3366	1.61	950000	2.3084
2.3604	1.62	960000	2.3084
2.3662	1.64	970000	2.3082
2.3754	1.66	980000	2.3085
2.3966	1.67	990000	2.3083
2.3537	1.69	1000000	2.3083
2.4711	1.71	1010000	2.3084
2.335	1.72	1020000	2.3082
2.3608	1.74	1030000	2.3082
2.3669	1.76	1040000	2.3080
2.463	1.78	1050000	2.3081
2.3369	1.79	1060000	2.3082
2.3314	1.81	1070000	2.3082
2.3681	1.83	1080000	2.3081
2.3867	1.84	1090000	2.3081
2.4012	1.86	1100000	2.3081
2.367	1.88	1110000	2.3080
2.415	1.89	1120000	2.3080
2.3738	1.91	1130000	2.3080
2.4199	1.93	1140000	2.3080
2.3884	1.94	1150000	2.3080
2.3609	1.96	1160000	2.3080
2.3343	1.98	1170000	2.3080
2.3575	1.99	1180000	2.3079
2.4116	2.01	1190000	2.3079
2.3074	2.03	1200000	2.3080
2.4261	2.05	1210000	2.3080
2.3793	2.06	1220000	2.3079
2.3543	2.08	1230000	2.3080
2.404	2.1	1240000	2.3081
2.4234	2.11	1250000	2.3079
2.3582	2.13	1260000	2.3080
2.3922	2.15	1270000	2.3079
2.3461	2.16	1280000	2.3080
2.3395	2.18	1290000	2.3080
2.3755	2.2	1300000	2.3080
2.3718	2.21	1310000	2.3079
2.3894	2.23	1320000	2.3079
2.3955	2.25	1330000	2.3079
2.3445	2.27	1340000	2.3079
2.3894	2.28	1350000	2.3080
2.3648	2.3	1360000	2.3080
2.3999	2.32	1370000	2.3080
2.3102	2.33	1380000	2.3079
2.3311	2.35	1390000	2.3078
2.3408	2.37	1400000	2.3079
2.3844	2.38	1410000	2.3080
2.3825	2.4	1420000	2.3080
2.398	2.42	1430000	2.3080
2.3305	2.43	1440000	2.3080
2.4646	2.45	1450000	2.3078
2.4326	2.47	1460000	2.3080
2.351	2.49	1470000	2.3080
2.4074	2.5	1480000	2.3080
2.3806	2.52	1490000	2.3080
2.4329	2.54	1500000	2.3080
2.421	2.55	1510000	2.3079
2.3322	2.57	1520000	2.3079
2.393	2.59	1530000	2.3079
2.3183	2.6	1540000	2.3080
2.3257	2.62	1550000	2.3080
2.3745	2.64	1560000	2.3080
2.409	2.65	1570000	2.3080
2.4447	2.67	1580000	2.3078
2.3805	2.69	1590000	2.3079
2.4323	2.7	1600000	2.3079
2.3654	2.72	1610000	2.3079
2.4017	2.74	1620000	2.3079
2.3168	2.76	1630000	2.3079
2.3304	2.77	1640000	2.3079
2.4072	2.79	1650000	2.3080
2.3232	2.81	1660000	2.3080
2.3563	2.82	1670000	2.3079
2.4327	2.84	1680000	2.3080
2.3932	2.86	1690000	2.3080
2.3134	2.87	1700000	2.3079
2.3421	2.89	1710000	2.3080
2.4805	2.91	1720000	2.3080
2.4306	2.92	1730000	2.3079
2.3511	2.94	1740000	2.3081
2.3509	2.96	1750000	2.3080
2.3598	2.98	1760000	2.3080
2.4583	2.99	1770000	2.3080

Framework versions

PEFT 0.8.2
Transformers 4.38.1
Pytorch 2.2.0+cu118
Datasets 2.17.1
Tokenizers 0.15.2

Library: peft
Created: Jan 24, 2024
Updated: Mar 1, 2024