bert-zs-sentence-classifier

juancavallotti/bert-zs-sentence-classifier

bert-zs-sentence-classifier is a text classification model from juancavallotti. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.

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

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At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: May 23, 2022
Updated: May 23, 2022
SHA: a131bbdb

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Model card

From the Hugging Face model README

bert-zs-sentence-classifier

This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3663
F1: 0.8483

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: 1e-05
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	F1
0.5973	0.01	500	0.5186	0.7538
0.5021	0.03	1000	0.4646	0.7996
0.4741	0.04	1500	0.4634	0.8064
0.4656	0.06	2000	0.4485	0.8142
0.4567	0.07	2500	0.4345	0.8160
0.4448	0.09	3000	0.4239	0.8228
0.4403	0.1	3500	0.4155	0.8294
0.4163	0.12	4000	0.4021	0.8290
0.4205	0.13	4500	0.4057	0.8283
0.416	0.14	5000	0.4049	0.8319
0.4115	0.16	5500	0.4095	0.8280
0.4156	0.17	6000	0.3927	0.8349
0.4042	0.19	6500	0.4003	0.8392
0.4057	0.2	7000	0.3929	0.8385
0.3977	0.22	7500	0.3915	0.8406
0.4049	0.23	8000	0.3785	0.8433
0.4027	0.24	8500	0.3807	0.8424
0.4096	0.26	9000	0.3768	0.8435
0.3958	0.27	9500	0.3846	0.8420
0.4037	0.29	10000	0.3808	0.8381
0.3813	0.3	10500	0.4004	0.8415
0.3934	0.32	11000	0.3821	0.8422
0.3895	0.33	11500	0.3844	0.8428
0.3907	0.35	12000	0.3847	0.8435
0.3862	0.36	12500	0.3803	0.8431
0.3958	0.37	13000	0.3739	0.8392
0.3845	0.39	13500	0.3817	0.8422
0.3914	0.4	14000	0.3857	0.8424
0.3814	0.42	14500	0.3793	0.8438
0.3816	0.43	15000	0.3843	0.8395
0.4022	0.45	15500	0.3737	0.8436
0.3879	0.46	16000	0.3750	0.8424
0.3794	0.48	16500	0.3743	0.8410
0.393	0.49	17000	0.3733	0.8461
0.384	0.5	17500	0.3765	0.8476
0.3782	0.52	18000	0.3748	0.8451
0.3931	0.53	18500	0.3807	0.8454
0.3889	0.55	19000	0.3653	0.8463
0.386	0.56	19500	0.3707	0.8445
0.3802	0.58	20000	0.3700	0.8474
0.3883	0.59	20500	0.3646	0.8463
0.3825	0.61	21000	0.3665	0.8513
0.382	0.62	21500	0.3620	0.8508
0.3795	0.63	22000	0.3692	0.8493
0.367	0.65	22500	0.3704	0.8479
0.3825	0.66	23000	0.3723	0.8472
0.3902	0.68	23500	0.3681	0.8465
0.3813	0.69	24000	0.3668	0.8515
0.3878	0.71	24500	0.3632	0.8506
0.3743	0.72	25000	0.3728	0.8463
0.3826	0.73	25500	0.3746	0.8465
0.3892	0.75	26000	0.3602	0.8518
0.3767	0.76	26500	0.3722	0.8513
0.3724	0.78	27000	0.3716	0.8499
0.3767	0.79	27500	0.3651	0.8483
0.3846	0.81	28000	0.3753	0.8493
0.3748	0.82	28500	0.3720	0.8458
0.3768	0.84	29000	0.3663	0.8508
0.3716	0.85	29500	0.3635	0.8531
0.3673	0.86	30000	0.3659	0.8485
0.3805	0.88	30500	0.3608	0.8518
0.3718	0.89	31000	0.3695	0.8520
0.374	0.91	31500	0.3631	0.8485
0.3871	0.92	32000	0.3659	0.8485
0.3724	0.94	32500	0.3584	0.8518
0.3756	0.95	33000	0.3587	0.8492
0.3709	0.97	33500	0.3700	0.8488
0.376	0.98	34000	0.3657	0.8492
0.372	0.99	34500	0.3663	0.8483

Framework versions

Transformers 4.19.2
Pytorch 1.11.0+cu113
Datasets 2.2.2
Tokenizers 0.12.1

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: May 23, 2022
Updated: May 23, 2022