indic-bert-finetuned-TRAC-DS

This model is a fine-tuned version of ai4bharat/indic-bert on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.9922
• Accuracy: 0.5825
• Precision: 0.5493
• Recall: 0.5412
• F1: 0.5428

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: 1e-06
• train_batch_size: 32
• eval_batch_size: 32
• seed: 43
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
1.0755	1.99	612	1.0346	0.5057	0.4072	0.4554	0.3806
1.0175	3.99	1224	1.0096	0.5678	0.6135	0.5011	0.4422
0.9974	5.98	1836	1.0010	0.5776	0.5637	0.5140	0.4799
0.9812	7.97	2448	0.9960	0.5694	0.5426	0.5283	0.5298
0.9675	9.97	3060	0.9956	0.5776	0.5565	0.5422	0.5442
0.9542	11.96	3672	0.9925	0.5882	0.5601	0.5420	0.5419
0.944	13.95	4284	0.9907	0.5866	0.5525	0.5441	0.5454
0.9347	15.95	4896	0.9921	0.5858	0.5527	0.5441	0.5456
0.9271	17.94	5508	0.9906	0.5931	0.5596	0.5482	0.5490
0.9236	19.93	6120	0.9922	0.5825	0.5493	0.5412	0.5428

Framework versions

• Transformers 4.20.1
• Pytorch 1.10.1+cu111
• Datasets 2.3.2
• Tokenizers 0.12.1