bert_sm_cv_defined_summarized_4

wiorz/bert_sm_cv_defined_summarized_4

bert_sm_cv_defined_summarized_4 is a text classification model from wiorz. 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: Jun 8, 2023
Updated: Jun 8, 2023
SHA: 3e9d3db2

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Model card

From the Hugging Face model README

bert_sm_cv_defined_summarized_4

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

Loss: 1.8001
Accuracy: 0.801
Precision: 0.4677
Recall: 0.1487
F1: 0.2257
D-index: 1.4847

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 8000
num_epochs: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	D-index
No log	1.0	250	0.4931	0.805	0.5	0.0308	0.0580	1.4481
0.5724	2.0	500	0.4850	0.806	0.5263	0.0513	0.0935	1.4569
0.5724	3.0	750	0.4842	0.811	0.6	0.0923	0.16	1.4785
0.4468	4.0	1000	0.4954	0.81	0.5806	0.0923	0.1593	1.4771
0.4468	5.0	1250	0.5307	0.81	0.5862	0.0872	0.1518	1.4753
0.381	6.0	1500	0.5312	0.809	0.5455	0.1231	0.2008	1.4866
0.381	7.0	1750	0.5354	0.807	0.5161	0.1641	0.2490	1.4983
0.283	8.0	2000	0.7003	0.811	0.6364	0.0718	0.1290	1.4712
0.283	9.0	2250	0.7079	0.798	0.4568	0.1897	0.2681	1.4949
0.1621	10.0	2500	0.9032	0.8	0.4603	0.1487	0.2248	1.4833
0.1621	11.0	2750	1.0875	0.797	0.4474	0.1744	0.2509	1.4881
0.0678	12.0	3000	1.2256	0.769	0.3861	0.3128	0.3456	1.4975
0.0678	13.0	3250	1.6378	0.793	0.4	0.1231	0.1882	1.4645
0.039	14.0	3500	1.7475	0.767	0.2841	0.1282	0.1767	1.4301
0.039	15.0	3750	1.8575	0.804	0.4848	0.0821	0.1404	1.4652
0.0295	16.0	4000	1.8151	0.775	0.3370	0.1590	0.2160	1.4522
0.0295	17.0	4250	1.8788	0.795	0.4219	0.1385	0.2085	1.4728
0.0416	18.0	4500	1.8193	0.765	0.3462	0.2308	0.2769	1.4636
0.0416	19.0	4750	1.6942	0.788	0.3896	0.1538	0.2206	1.4685
0.0322	20.0	5000	1.8001	0.801	0.4677	0.1487	0.2257	1.4847

Framework versions

Transformers 4.28.0
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Jun 8, 2023
Updated: Jun 8, 2023