distilbert-base-uncased-finetune

rdchambers/distilbert-base-uncased-finetune

distilbert-base-uncased-finetune is a token classification model from rdchambers. 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. --

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At a glance

Task: Token Classification
Library: transformers
License: apache-2.0
Model type: distilbert
Access: Public
Created: Apr 27, 2022
Updated: Apr 27, 2022
SHA: 3182a7cf

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Model card

From the Hugging Face model README

distilbert-base-uncased-finetune

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: 0.0149
Precision: 0.8458
Recall: 0.8060
F1: 0.8255
Accuracy: 0.9954

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: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	48	0.0556	0.5372	0.1902	0.2809	0.9838
No log	2.0	96	0.0171	0.8320	0.8023	0.8169	0.9951
No log	3.0	144	0.0149	0.8458	0.8060	0.8255	0.9954

Framework versions

Transformers 4.18.0
Pytorch 1.11.0
Datasets 2.1.0
Tokenizers 0.12.1

Task: Token Classification
Library: transformers
Type: distilbert
License: apache-2.0
Created: Apr 27, 2022
Updated: Apr 27, 2022