pp_wnut_model

PradhyumnaPoralla/pp_wnut_model

pp_wnut_model is a token classification model from PradhyumnaPoralla. Use it when you need labels on individual words, such as names. 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. --

Downloads · 30 days

22% of all-time downloads

All-time downloads

Public

Parameters

66.4M

531 MB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors266 MB · 100%

At a glance

Task: Token Classification
Library: transformers
License: apache-2.0
Model type: distilbert
Access: Public
Created: Jun 16, 2024
Updated: Jun 16, 2024
SHA: 1bfe66d9

Try a prompt

Base models

distilbert/distilbert-base-uncased

Datasets

wnut_17

Model card

From the Hugging Face model README

pp_wnut_model

This model is a fine-tuned version of distilbert/distilbert-base-uncased on the wnut_17 dataset. It achieves the following results on the evaluation set:

Loss: 0.2734
Precision: 0.5696
Recall: 0.2956
F1: 0.3893
Accuracy: 0.9416

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	Precision	Recall	F1	Accuracy
No log	1.0	213	0.2813	0.5089	0.2382	0.3245	0.9381
No log	2.0	426	0.2734	0.5696	0.2956	0.3893	0.9416

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu118
Datasets 2.19.0
Tokenizers 0.19.1

Task: Token Classification
Library: transformers
Type: distilbert
License: apache-2.0
Created: Jun 16, 2024
Updated: Jun 16, 2024