Q2-PHQ

ishwarbb23/Q2-PHQ

Q2-PHQ is a text classification model from ishwarbb23. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.

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

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At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: distilbert
Access: Public
Created: Nov 2, 2023
Updated: Nov 4, 2023
SHA: e044a130

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Base models

Model card

From the Hugging Face model README

Q2-PHQ

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.5669
Accuracy: 0.82
Mcc: 0.3059

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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Mcc
No log	1.0	51	0.4262	0.84	0.2085
No log	2.0	102	0.4447	0.815	0.3286
No log	3.0	153	0.4965	0.81	0.2935
No log	4.0	204	0.5477	0.82	0.2335
No log	5.0	255	0.5669	0.82	0.3059

Framework versions

Transformers 4.35.0
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1

Task: Text Classification
Library: transformers
Type: distilbert
License: apache-2.0
Created: Nov 2, 2023
Updated: Nov 4, 2023