results

Gkumi/results

results is a token classification model from Gkumi. 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: Jun 21, 2024
Updated: Jun 21, 2024
SHA: 9ee44178

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Base models

Model card

From the Hugging Face model README

results

This model is a fine-tuned version of distilbert-base-cased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0452
Precision: 0.8809
Recall: 0.9161
F1: 0.8982
Accuracy: 0.9860

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: 0.0005
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	Precision	Recall	F1	Accuracy
0.1732	1.0	2180	0.1202	0.5106	0.6557	0.5741	0.9612
0.1057	2.0	4360	0.0821	0.6500	0.7866	0.7118	0.9728
0.0639	3.0	6540	0.0573	0.7953	0.8256	0.8102	0.9812
0.0347	4.0	8720	0.0482	0.8531	0.9030	0.8773	0.9846
0.0212	5.0	10900	0.0452	0.8809	0.9161	0.8982	0.9860

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1

Task: Token Classification
Library: transformers
Type: distilbert
License: apache-2.0
Created: Jun 21, 2024
Updated: Jun 21, 2024