rubert-base-cased-conversational_ner-v3

Data-Lab/rubert-base-cased-conversational_ner-v3

rubert-base-cased-conversational_ner-v3 is a token classification model from Data-Lab. Use it when you need labels on individual words, such as names. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

Downloads · 30 days

1% of all-time downloads

All-time downloads

3.7K

Public

Repo size

1.4 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin709 MB · 99%

At a glance

Task: Token Classification
Library: transformers
Model type: bert
Access: Public
Created: Nov 11, 2023
Updated: Nov 11, 2023
SHA: 46a111af

Try a prompt

Base models

DeepPavlov/rubert-base-cased-conversational

Model card

From the Hugging Face model README

rubert-base-cased-conversational_ner-v3

This model is a fine-tuned version of DeepPavlov/rubert-base-cased-conversational on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1204
Precision: 0.7484
Recall: 0.7987
F1: 0.7727
Accuracy: 0.9242

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	75	0.2186	0.4860	0.5839	0.5305	0.8634
No log	2.0	150	0.1380	0.6886	0.7718	0.7278	0.9200
No log	3.0	225	0.1204	0.7484	0.7987	0.7727	0.9242

Framework versions

Transformers 4.33.1
Pytorch 2.0.1
Datasets 2.14.4
Tokenizers 0.13.3

Task: Token Classification
Library: transformers
Type: bert
Created: Nov 11, 2023
Updated: Nov 11, 2023