week5-eng-distilbert-base-multilingual-cased-finetuned

ensw/week5-eng-distilbert-base-multilingual-cased-finetuned

week5-eng-distilbert-base-multilingual-cased-finetuned is a token classification model from ensw. 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: Oct 31, 2022
Updated: Oct 31, 2022
SHA: e3ec4080

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Model card

From the Hugging Face model README

week5-eng-distilbert-base-multilingual-cased-finetuned

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

Loss: 0.0855
Precision: 0.2813
Recall: 0.2949
F1: 0.2880
Accuracy: 0.9763

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
0.1071	1.0	924	0.0911	0.2472	0.0444	0.0753	0.9755
0.07	2.0	1848	0.0891	0.3206	0.1697	0.2219	0.9775
0.0522	3.0	2772	0.0855	0.2813	0.2949	0.2880	0.9763

Framework versions

Transformers 4.23.1
Pytorch 1.12.1+cu113
Datasets 2.6.1
Tokenizers 0.13.1

Task: Token Classification
Library: transformers
Type: distilbert
License: apache-2.0
Created: Oct 31, 2022
Updated: Oct 31, 2022