roberta_reman

gustavecortal/roberta_reman

roberta_reman is a text classification model from gustavecortal. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.

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

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At a glance

Task: Text Classification
Library: transformers
License: mit
Model type: roberta
Access: Public
Created: Dec 23, 2022
Updated: Dec 23, 2022
SHA: 3de64985

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Model card

From the Hugging Face model README

roberta_reman

This model is a fine-tuned version of ibm/ColD-Fusion on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.4272
F1: 0.7004
Roc Auc: 0.7862
Accuracy: 0.4330
Recall: 0.6831
Precision: 0.7185

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy	Recall	Precision
No log	1.0	113	0.4673	0.5668	0.6955	0.2990	0.4930	0.6667
No log	2.0	226	0.4187	0.6397	0.7403	0.3918	0.5563	0.7524
No log	3.0	339	0.4272	0.7004	0.7862	0.4330	0.6831	0.7185
No log	4.0	452	0.4191	0.6566	0.7539	0.3918	0.6127	0.7073
0.3529	5.0	565	0.4246	0.6788	0.7706	0.4124	0.6549	0.7045

Framework versions

Transformers 4.25.1
Pytorch 1.13.1+rocm5.2
Datasets 2.8.0
Tokenizers 0.13.2

Task: Text Classification
Library: transformers
Type: roberta
License: mit
Created: Dec 23, 2022
Updated: Dec 23, 2022