ChemBERTa_drug_state_classification

nepp1d0/ChemBERTa_drug_state_classification

ChemBERTa_drug_state_classification is a text classification model from nepp1d0. 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: Mar 2, 2022
Updated: Apr 13, 2022
SHA: 080708b8

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Model card

From the Hugging Face model README

ChemBERTa_drug_state_classification

This model is a fine-tuned version of nepp1d0/ChemBERTa_drug_state_classification on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0463
Accuracy: 0.9870

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: 0.0001
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5063	1.0	240	0.3069	0.9160
0.3683	2.0	480	0.2135	0.9431
0.2633	3.0	720	0.1324	0.9577
0.1692	4.0	960	0.0647	0.9802
0.1109	5.0	1200	0.0463	0.9870

Framework versions

Transformers 4.18.0
Pytorch 1.10.0+cu111
Datasets 2.0.0
Tokenizers 0.12.1

Task: Text Classification
Library: transformers
Type: roberta
Created: Mar 2, 2022
Updated: Apr 13, 2022