indic-bert-FakeNews-Dravidiant – AI Model by mdosama39 | AlphaNeural AI

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mdosama39/
indic-bert-FakeNews-Dravidiant

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text-classification

generated_from_trainer

ai4bharat/indic-bert

autotrain_compatible

endpoints_compatible

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indic-bert-FakeNews-Dravidiant

This model is a fine-tuned version of ai4bharat/indic-bert on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.6230
Accuracy: 0.6822
Weighted f1 score: 0.6816
Macro f1 score: 0.6816

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-06
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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Weighted f1 score	Macro f1 score
1.0142	1.0	204	0.7823	0.5509	0.5402	0.5405
0.7202	2.0	408	0.6967	0.5902	0.5747	0.5744
0.6758	3.0	612	0.6730	0.6319	0.6224	0.6221
0.6471	4.0	816	0.6547	0.6417	0.6336	0.6334
0.6221	5.0	1020	0.6396	0.6663	0.6646	0.6645
0.6005	6.0	1224	0.6322	0.6724	0.6723	0.6723
0.5801	7.0	1428	0.6385	0.6601	0.6530	0.6528
0.5613	8.0	1632	0.6249	0.6810	0.6797	0.6796
0.5534	9.0	1836	0.6231	0.6834	0.6831	0.6831
0.5428	10.0	2040	0.6230	0.6822	0.6816	0.6816

Framework versions

Transformers 4.35.0
Pytorch 2.0.0
Datasets 2.11.0
Tokenizers 0.14.1