SA-roberta-e3-w1-1.5-b16-mt4-w0.01-data2

YanJiangJerry/SA-roberta-e3-w1-1.5-b16-mt4-w0.01-data2

SA-roberta-e3-w1-1.5-b16-mt4-w0.01-data2 is a text classification model from YanJiangJerry. Use it when you need a label for a piece of text. It is set up for transformers.

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

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At a glance

Task: Text Classification
Library: transformers
Model type: roberta
Access: Public
Created: Jul 14, 2023
Updated: Jul 14, 2023
SHA: 4748c984

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Model card

From the Hugging Face model README

SA-roberta-e3-w1-1.5-b16-mt4-w0.01-data2

This model is a fine-tuned version of Amalq/autotrain-smm4h_large_roberta_clean-874027878 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.5675
Accuracy: 0.9121
F1: 0.8819
Precision: 0.8832
Recall: 0.8806

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.3096	1.0	581	0.3382	0.9077	0.8770	0.8706	0.8836
0.1202	2.0	1162	0.5246	0.9032	0.8730	0.8543	0.8925
0.0655	3.0	1743	0.5675	0.9121	0.8819	0.8832	0.8806

Framework versions

Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3

Task: Text Classification
Library: transformers
Type: roberta
Created: Jul 14, 2023
Updated: Jul 14, 2023