distilbert-base-uncased-pytorch-issues-classifier

yajatpawar/distilbert-base-uncased-pytorch-issues-classifier

distilbert-base-uncased-pytorch-issues-classifier is a machine learning model from yajatpawar. Use it for the machine learning task on the model card, and read the license before you ship it in a product. 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

License: apache-2.0
Model type: distilbert
Access: Public
Created: Mar 9, 2026
Updated: Mar 10, 2026
SHA: 2e033387

Base models

Model card

From the Hugging Face model README

distilbert-base-uncased-pytorch-issues-classifier

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: 0.1250
F1 Micro: 0.6960
F1 Macro: 0.2629
F1 Weighted: 0.6287
F1 Samples: 0.6492
Precision Micro: 0.7690
Precision Macro: 0.2652
Recall Micro: 0.6356
Recall Macro: 0.2619
Subset Accuracy: 0.1883
Hamming Loss: 0.0463

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: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1 Micro	F1 Macro	F1 Weighted	F1 Samples	Precision Micro	Precision Macro	Recall Micro	Recall Macro	Subset Accuracy	Hamming Loss
0.2157	0.5203	500	0.2007	0.3763	0.0643	0.2856	0.3039	0.6629	0.0942	0.2627	0.0583	0.0260	0.0726
0.1622	1.0406	1000	0.1538	0.5910	0.1681	0.5137	0.5324	0.7259	0.2445	0.4983	0.1575	0.0780	0.0575
0.1376	1.5609	1500	0.1372	0.6663	0.2453	0.6019	0.6204	0.7417	0.2602	0.6049	0.2393	0.1691	0.0505
0.1316	2.0812	2000	0.1288	0.6877	0.2599	0.6209	0.6388	0.7568	0.2625	0.6301	0.2589	0.1811	0.0477
0.1226	2.6015	2500	0.1250	0.6960	0.2629	0.6287	0.6492	0.7690	0.2652	0.6356	0.2619	0.1883	0.0463

Framework versions

Transformers 4.44.0
Pytorch 2.10.0+cu128
Datasets 2.18.0
Tokenizers 0.19.1

Type: distilbert
License: apache-2.0
Created: Mar 9, 2026
Updated: Mar 10, 2026