copilot_relex_v1

bobbyw/copilot_relex_v1

copilot_relex_v1 is a text classification model from bobbyw. Use it when you need a label for a piece of text. It is set up for transformers. 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

Task: Text Classification
Library: transformers
License: mit
Model type: deberta-v2
Access: Public
Created: Nov 14, 2023
Updated: May 1, 2024
SHA: c607ec4c

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Base models

microsoft/deberta-v3-small

Model card

From the Hugging Face model README

copilot_relex_v1

This model is a fine-tuned version of microsoft/deberta-v3-small on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.0134
Accuracy: 0.0038
F1: 0.0062
Precision: 0.0031
Recall: 0.625
Learning Rate: 0.0

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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall	Rate
No log	1.0	20	0.5469	0.0994	0.0093	0.0047	0.8438	0.0000
No log	2.0	40	0.3859	0.0050	0.0100	0.0050	1.0	0.0000
No log	3.0	60	0.2662	0.0050	0.0100	0.0050	1.0	0.0000
No log	4.0	80	0.1781	0.0050	0.0100	0.0050	1.0	0.0000
No log	5.0	100	0.1183	0.0050	0.0100	0.0050	1.0	0.0000
No log	6.0	120	0.0823	0.0050	0.0100	0.0050	1.0	0.0000
No log	7.0	140	0.0614	0.0050	0.0100	0.0050	1.0	0.0000
No log	8.0	160	0.0494	0.0050	0.0100	0.0050	1.0	0.0000
No log	9.0	180	0.0423	0.0050	0.0100	0.0050	1.0	0.0000
No log	10.0	200	0.0379	0.0050	0.0100	0.0050	1.0	0.0000
No log	11.0	220	0.0350	0.0050	0.0100	0.0050	1.0	0.0000
No log	12.0	240	0.0331	0.0050	0.0100	0.0050	1.0	0.0000
No log	13.0	260	0.0318	0.0050	0.0100	0.0050	1.0	0.0000
No log	14.0	280	0.0307	0.0050	0.0100	0.0050	1.0	0.0000
No log	15.0	300	0.0300	0.0050	0.0100	0.0050	1.0	0.0000
No log	16.0	320	0.0294	0.0050	0.0100	0.0050	1.0	0.0000
No log	17.0	340	0.0290	0.0050	0.0100	0.0050	1.0	0.0000
No log	18.0	360	0.0286	0.0050	0.0100	0.0050	1.0	0.0000
No log	19.0	380	0.0283	0.0050	0.0100	0.0050	1.0	0.0000
No log	20.0	400	0.0300	0.0050	0.0100	0.0050	1.0	0.0000
No log	21.0	420	0.0290	0.0050	0.0100	0.0050	1.0	0.0000
No log	22.0	440	0.0252	0.0050	0.0100	0.0050	1.0	0.0000
No log	23.0	460	0.0246	0.0050	0.0100	0.0050	1.0	0.0000
No log	24.0	480	0.0242	0.0050	0.0100	0.0050	1.0	0.0000
0.1127	25.0	500	0.0239	0.0050	0.0100	0.0050	1.0	0.0000
0.1127	26.0	520	0.0233	0.0050	0.0100	0.0050	1.0	0.0000
0.1127	27.0	540	0.0226	0.0050	0.0100	0.0050	1.0	0.0000
0.1127	28.0	560	0.0224	0.0050	0.0100	0.0050	1.0	0.0000
0.1127	29.0	580	0.0217	0.0050	0.0100	0.0050	1.0	0.0000
0.1127	30.0	600	0.0211	0.0047	0.0093	0.0047	0.9375	0.0000
0.1127	31.0	620	0.0206	0.0045	0.0090	0.0045	0.9062	0.0000
0.1127	32.0	640	0.0207	0.0047	0.0090	0.0045	0.9062	0.0000
0.1127	33.0	660	0.0198	0.0045	0.0090	0.0045	0.9062	0.0000
0.1127	34.0	680	0.0205	0.0047	0.0090	0.0045	0.9062	0.0000
0.1127	35.0	700	0.0193	0.0045	0.0090	0.0045	0.9062	0.0000
0.1127	36.0	720	0.0198	0.0045	0.0090	0.0045	0.9062	0.0000
0.1127	37.0	740	0.0190	0.0047	0.0090	0.0045	0.9062	0.0000
0.1127	38.0	760	0.0197	0.0049	0.0090	0.0045	0.9062	0.0000
0.1127	39.0	780	0.0185	0.0047	0.0090	0.0045	0.9062	0.0000
0.1127	40.0	800	0.0184	0.0045	0.0090	0.0045	0.9062	0.0000
0.1127	41.0	820	0.0188	0.0045	0.0090	0.0045	0.9062	0.0000
0.1127	42.0	840	0.0179	0.0045	0.0090	0.0045	0.9062	0.0000
0.1127	43.0	860	0.0178	0.0045	0.0090	0.0045	0.9062	0.0000
0.1127	44.0	880	0.0174	0.0045	0.0090	0.0045	0.9062	0.0000
0.1127	45.0	900	0.0182	0.0041	0.0081	0.0041	0.8125	0.0000
0.1127	46.0	920	0.0171	0.0045	0.0090	0.0045	0.9062	0.0000
0.1127	47.0	940	0.0168	0.0044	0.0087	0.0044	0.875	0.0000
0.1127	48.0	960	0.0167	0.0041	0.0081	0.0041	0.8125	0.0000
0.1127	49.0	980	0.0165	0.0039	0.0078	0.0039	0.7812	0.0000
0.0253	50.0	1000	0.0162	0.0039	0.0078	0.0039	0.7812	1e-05
0.0253	51.0	1020	0.0160	0.0041	0.0081	0.0041	0.8125	0.0000
0.0253	52.0	1040	0.0159	0.0038	0.0075	0.0038	0.75	0.0000
0.0253	53.0	1060	0.0158	0.0038	0.0075	0.0038	0.75	0.0000
0.0253	54.0	1080	0.0163	0.0041	0.0075	0.0038	0.75	0.0000
0.0253	55.0	1100	0.0160	0.0039	0.0072	0.0036	0.7188	9e-06
0.0253	56.0	1120	0.0161	0.0034	0.0069	0.0034	0.6875	0.0000
0.0253	57.0	1140	0.0156	0.0036	0.0069	0.0034	0.6875	0.0000
0.0253	58.0	1160	0.0154	0.0041	0.0069	0.0034	0.6875	0.0000
0.0253	59.0	1180	0.0155	0.0039	0.0072	0.0036	0.7188	0.0000
0.0253	60.0	1200	0.0155	0.0036	0.0069	0.0034	0.6875	0.0000
0.0253	61.0	1220	0.0154	0.0038	0.0069	0.0034	0.6875	0.0000
0.0253	62.0	1240	0.0156	0.0041	0.0069	0.0034	0.6875	0.0000
0.0253	63.0	1260	0.0152	0.0038	0.0069	0.0034	0.6875	0.0000
0.0253	64.0	1280	0.0146	0.0036	0.0069	0.0034	0.6875	0.0000
0.0253	65.0	1300	0.0147	0.0041	0.0069	0.0034	0.6875	7e-06
0.0253	66.0	1320	0.0149	0.0039	0.0066	0.0033	0.6562	0.0000
0.0253	67.0	1340	0.0148	0.0038	0.0062	0.0031	0.625	0.0000
0.0253	68.0	1360	0.0148	0.0039	0.0066	0.0033	0.6562	0.0000
0.0253	69.0	1380	0.0143	0.0041	0.0069	0.0034	0.6875	0.0000
0.0253	70.0	1400	0.0144	0.0039	0.0062	0.0031	0.625	6e-06
0.0253	71.0	1420	0.0145	0.0039	0.0066	0.0033	0.6562	0.0000
0.0253	72.0	1440	0.0141	0.0038	0.0066	0.0033	0.6562	0.0000
0.0253	73.0	1460	0.0144	0.0039	0.0066	0.0033	0.6562	0.0000
0.0253	74.0	1480	0.0144	0.0039	0.0066	0.0033	0.6562	0.0000
0.019	75.0	1500	0.0142	0.0036	0.0062	0.0031	0.625	5e-06
0.019	76.0	1520	0.0140	0.0041	0.0066	0.0033	0.6562	0.0000
0.019	77.0	1540	0.0139	0.0039	0.0066	0.0033	0.6562	0.0000
0.019	78.0	1560	0.0140	0.0039	0.0066	0.0033	0.6562	0.0000
0.019	79.0	1580	0.0139	0.0038	0.0059	0.0030	0.5938	0.0000
0.019	80.0	1600	0.0139	0.0039	0.0066	0.0033	0.6562	0.0000
0.019	81.0	1620	0.0139	0.0042	0.0066	0.0033	0.6562	0.0000
0.019	82.0	1640	0.0136	0.0036	0.0062	0.0031	0.625	0.0000
0.019	83.0	1660	0.0138	0.0041	0.0062	0.0031	0.625	0.0000
0.019	84.0	1680	0.0136	0.0039	0.0059	0.0030	0.5938	0.0000
0.019	85.0	1700	0.0136	0.0038	0.0059	0.0030	0.5938	3e-06
0.019	86.0	1720	0.0136	0.0038	0.0059	0.0030	0.5938	0.0000
0.019	87.0	1740	0.0133	0.0038	0.0062	0.0031	0.625	0.0000
0.019	88.0	1760	0.0137	0.0039	0.0059	0.0030	0.5938	0.0000
0.019	89.0	1780	0.0134	0.0036	0.0059	0.0030	0.5938	0.0000
0.019	90.0	1800	0.0133	0.0038	0.0059	0.0030	0.5938	0.0000
0.019	91.0	1820	0.0137	0.0041	0.0066	0.0033	0.6562	0.0000
0.019	92.0	1840	0.0134	0.0038	0.0059	0.0030	0.5938	0.0000
0.019	93.0	1860	0.0135	0.0038	0.0059	0.0030	0.5938	0.0000
0.019	94.0	1880	0.0134	0.0038	0.0062	0.0031	0.625	0.0000
0.019	95.0	1900	0.0136	0.0039	0.0059	0.0030	0.5938	0.0000
0.019	96.0	1920	0.0135	0.0039	0.0059	0.0030	0.5938	0.0000
0.019	97.0	1940	0.0134	0.0038	0.0062	0.0031	0.625	0.0000
0.019	98.0	1960	0.0134	0.0038	0.0062	0.0031	0.625	0.0000
0.019	99.0	1980	0.0134	0.0038	0.0062	0.0031	0.625	0.0000
0.0156	100.0	2000	0.0134	0.0038	0.0062	0.0031	0.625	0.0

Framework versions

Transformers 4.40.1
Pytorch 2.2.1+cu121
Datasets 2.19.0
Tokenizers 0.19.1

Task: Text Classification
Library: transformers
Type: deberta-v2
License: mit
Created: Nov 14, 2023
Updated: May 1, 2024