distilbert-classification-10ksamples

jayavibhav/distilbert-classification-10ksamples

distilbert-classification-10ksamples is a text classification model from jayavibhav. 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: Aug 9, 2023
Updated: Aug 9, 2023
SHA: 98c5e86e

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Base models

Model card

From the Hugging Face model README

distilbert-classification-10ksamples

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1977
Accuracy: 0.96

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: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1853	1.0	625	0.1682	0.9577
0.0436	2.0	1250	0.1977	0.96

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3

Task: Text Classification
Library: transformers
Type: distilbert
License: apache-2.0
Created: Aug 9, 2023
Updated: Aug 9, 2023