SA-tweet-bert-large-e6-w1-1.5

YanJiangJerry/SA-tweet-bert-large-e6-w1-1.5

SA-tweet-bert-large-e6-w1-1.5 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 12, 2023
Updated: Jul 12, 2023
SHA: e65012b5

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Model card

From the Hugging Face model README

SA-tweet-bert-large-e6-w1-1.5

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: 0.9227
Accuracy: 0.9066
F1: 0.8688
Precision: 0.9115
Recall: 0.8299

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: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.4119	1.0	2321	0.6382	0.8943	0.8601	0.8488	0.8716
0.2178	2.0	4642	0.6811	0.8888	0.8571	0.8219	0.8955
0.1101	3.0	6963	0.7734	0.8910	0.8604	0.8229	0.9015
0.0234	4.0	9284	0.7485	0.9066	0.8704	0.9010	0.8418
0.0333	5.0	11605	0.7888	0.9099	0.8796	0.8757	0.8836
0.0093	6.0	13926	0.9227	0.9066	0.8688	0.9115	0.8299

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 12, 2023
Updated: Jul 12, 2023