distilbert-base-uncased-finetuned-Pre_requisite_finder

satyamverma/distilbert-base-uncased-finetuned-Pre_requisite_finder

distilbert-base-uncased-finetuned-Pre_requisite_finder is a text classification model from satyamverma. 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: May 23, 2023
Updated: May 24, 2023
SHA: 44c80426

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Model card

From the Hugging Face model README

distilbert-base-uncased-finetuned-Pre_requisite_finder

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: 0.4156
Accuracy: 0.8177

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
0.4475	1.0	863	0.4156	0.8177
0.4247	2.0	1726	0.4152	0.8177
0.4191	3.0	2589	0.4100	0.8177
0.4259	4.0	3452	0.4125	0.8177
0.4143	5.0	4315	0.4247	0.8165

Framework versions

Transformers 4.28.0
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3

Task: Text Classification
Library: transformers
Type: distilbert
License: apache-2.0
Created: May 23, 2023
Updated: May 24, 2023