results

chiencn/results

results is a machine learning model from chiencn. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.

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

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Hugging Face

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At a glance

License: apache-2.0
Model type: bert
Access: Public
Created: Sep 17, 2024
Updated: Sep 19, 2024
SHA: 13819af9

Base models

Model card

From the Hugging Face model README

results

This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.5524
Precision: 0.6970
Recall: 0.6661
F1: 0.6798
Accuracy: 0.9081

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

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	250	0.2537	0.7645	0.5606	0.5850	0.9188
0.2695	2.0	500	0.2528	0.7559	0.6099	0.6464	0.9205
0.2695	3.0	750	0.2524	0.7359	0.6409	0.6729	0.9183
0.2201	4.0	1000	0.2660	0.7015	0.6596	0.6773	0.9099
0.2201	5.0	1250	0.2926	0.6924	0.6821	0.6870	0.9053
0.1629	6.0	1500	0.3055	0.6904	0.6848	0.6876	0.9042
0.1629	7.0	1750	0.3332	0.7037	0.6532	0.6736	0.9109
0.1144	8.0	2000	0.3661	0.6870	0.6759	0.6812	0.9038
0.1144	9.0	2250	0.3670	0.6950	0.6597	0.6750	0.9079
0.081	10.0	2500	0.4031	0.6969	0.6588	0.6751	0.9086
0.081	11.0	2750	0.4176	0.6883	0.6734	0.6804	0.9045
0.0611	12.0	3000	0.4531	0.7003	0.6552	0.6739	0.9098
0.0611	13.0	3250	0.4733	0.6970	0.6600	0.6758	0.9085
0.0476	14.0	3500	0.4815	0.6997	0.6533	0.6724	0.9098
0.0476	15.0	3750	0.5058	0.6977	0.6580	0.6748	0.9089
0.039	16.0	4000	0.5027	0.7011	0.6646	0.6804	0.9095
0.039	17.0	4250	0.5196	0.6993	0.6635	0.6790	0.9090
0.0309	18.0	4500	0.5462	0.6986	0.6687	0.6819	0.9085
0.0309	19.0	4750	0.5406	0.6939	0.6684	0.6799	0.9069
0.0273	20.0	5000	0.5524	0.6970	0.6661	0.6798	0.9081

Framework versions

Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 3.0.0
Tokenizers 0.19.1

Type: bert
License: apache-2.0
Created: Sep 17, 2024
Updated: Sep 19, 2024