TaNER-2k-indic_glue – AI Model by AnanthZeke | AlphaNeural AI

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AnanthZeke/
TaNER-2k-indic_glue

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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tabert-2k-indic_glue

This model is a fine-tuned version of livinNector/tabert-2k on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.2663
Precision: 0.7940
Recall: 0.8281
F1: 0.8107
Accuracy: 0.9164

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: 5e-05
train_batch_size: 32
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.5342	0.31	200	0.3755	0.6758	0.7277	0.7008	0.8753
0.3625	0.62	400	0.3276	0.7279	0.7920	0.7586	0.8914
0.3065	0.94	600	0.2855	0.7827	0.7980	0.7903	0.9050
0.2321	1.25	800	0.2804	0.7860	0.8063	0.7960	0.9092
0.1849	1.56	1000	0.2735	0.7946	0.8154	0.8049	0.9143
0.1784	1.88	1200	0.2663	0.7940	0.8281	0.8107	0.9164

Framework versions

Transformers 4.29.2
Pytorch 2.0.0+cu118
Datasets 2.12.0
Tokenizers 0.13.3