bert-base-uncased-tajik-ner

muhtasham/bert-base-uncased-tajik-ner

bert-base-uncased-tajik-ner is a token classification model from muhtasham. 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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Base models

Datasets

wikiann

Model card

From the Hugging Face model README

bert-base-uncased-tajik-ner

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

Loss: 1.2137
Precision: 0.5042
Recall: 0.5769
F1: 0.5381
Accuracy: 0.8481

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: 200

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	2.0	50	0.9499	0.0450	0.0962	0.0613	0.6626
No log	4.0	100	0.7348	0.1549	0.2115	0.1789	0.7401
No log	6.0	150	0.6685	0.1916	0.3077	0.2362	0.8017
No log	8.0	200	0.7875	0.3923	0.4904	0.4359	0.8036
No log	10.0	250	0.7495	0.4225	0.5769	0.4878	0.8274
No log	12.0	300	0.8934	0.4198	0.5288	0.4681	0.8085
No log	14.0	350	0.9455	0.4758	0.5673	0.5175	0.8236
No log	16.0	400	0.9469	0.5893	0.6346	0.6111	0.8410
No log	18.0	450	0.9936	0.5333	0.6154	0.5714	0.8485
0.2726	20.0	500	0.9804	0.5	0.6058	0.5478	0.8519
0.2726	22.0	550	1.1035	0.5963	0.625	0.6103	0.8432
0.2726	24.0	600	1.0318	0.5856	0.625	0.6047	0.8576
0.2726	26.0	650	1.1820	0.4921	0.5962	0.5391	0.8221
0.2726	28.0	700	1.1204	0.4878	0.5769	0.5286	0.8311
0.2726	30.0	750	1.1911	0.5357	0.5769	0.5556	0.8376
0.2726	32.0	800	1.1747	0.5259	0.5865	0.5545	0.8394
0.2726	34.0	850	1.1403	0.5872	0.6154	0.6009	0.8542
0.2726	36.0	900	1.1824	0.5370	0.5577	0.5472	0.8330
0.2726	38.0	950	1.1467	0.5424	0.6154	0.5766	0.8440
0.003	40.0	1000	1.2148	0.5268	0.5673	0.5463	0.8360
0.003	42.0	1050	1.3478	0.5273	0.5577	0.5421	0.8266
0.003	44.0	1100	1.2137	0.5042	0.5769	0.5381	0.8481

Framework versions

Transformers 4.21.2
Pytorch 1.12.1+cu113
Datasets 2.4.0
Tokenizers 0.12.1

Task: Token Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Aug 26, 2022
Updated: Sep 13, 2023