fine-tuning-Phi2-with-webglm-qa-with-lora_4

Gunslinger3D/fine-tuning-Phi2-with-webglm-qa-with-lora_4

fine-tuning-Phi2-with-webglm-qa-with-lora_4 is a machine learning model from Gunslinger3D. 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 mit.

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

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Hugging Face

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At a glance

Library: peft
License: mit
Access: Public
Created: Mar 11, 2024
Updated: Mar 13, 2024
SHA: cc8e8e4c

Base models

microsoft/phi-2

Model card

From the Hugging Face model README

fine-tuning-Phi2-with-webglm-qa-with-lora_4

This model is a fine-tuned version of microsoft/phi-2 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1176

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: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 5
total_train_batch_size: 10
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
training_steps: 500
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
8.1178	0.2	10	7.7550
7.3762	0.4	20	6.3827
4.9217	0.6	30	3.2172
1.7792	0.8	40	0.6700
0.5779	1.0	50	0.5969
0.4824	1.2	60	0.5149
0.4689	1.39	70	0.4440
0.3833	1.59	80	0.3862
0.2916	1.79	90	0.3364
0.2435	1.99	100	0.3013
0.2538	2.19	110	0.2779
0.2147	2.39	120	0.2619
0.1982	2.59	130	0.2453
0.2183	2.79	140	0.2275
0.1737	2.99	150	0.2148
0.1794	3.19	160	0.2068
0.1692	3.39	170	0.1949
0.1573	3.59	180	0.1864
0.1478	3.78	190	0.1788
0.164	3.98	200	0.1732
0.1454	4.18	210	0.1676
0.1279	4.38	220	0.1653
0.1544	4.58	230	0.1595
0.1206	4.78	240	0.1524
0.1334	4.98	250	0.1486
0.1342	5.18	260	0.1472
0.1061	5.38	270	0.1442
0.1265	5.58	280	0.1427
0.131	5.78	290	0.1389
0.1067	5.98	300	0.1374
0.1158	6.18	310	0.1331
0.1114	6.37	320	0.1323
0.1104	6.57	330	0.1311
0.108	6.77	340	0.1281
0.1015	6.97	350	0.1271
0.1	7.17	360	0.1262
0.1091	7.37	370	0.1242
0.1013	7.57	380	0.1230
0.1074	7.77	390	0.1233
0.0946	7.97	400	0.1226
0.0854	8.17	410	0.1222
0.0914	8.37	420	0.1205
0.1117	8.57	430	0.1198
0.0922	8.76	440	0.1194
0.1012	8.96	450	0.1185
0.0964	9.16	460	0.1185
0.0948	9.36	470	0.1181
0.0943	9.56	480	0.1178
0.0915	9.76	490	0.1176
0.0924	9.96	500	0.1176

Framework versions

PEFT 0.7.1
Transformers 4.36.2
Pytorch 2.0.0
Datasets 2.15.0
Tokenizers 0.15.0

Library: peft
License: mit
Created: Mar 11, 2024
Updated: Mar 13, 2024