hing-roberta-finetuned-non-code-mixed-DS

This model is a fine-tuned version of l3cube-pune/hing-roberta on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.1286
• Accuracy: 0.6656
• Precision: 0.6575
• Recall: 0.6554
• F1: 0.6556

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: 2.824279936868144e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 43
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.8233	2.0	926	0.8104	0.6656	0.6607	0.6537	0.6555
0.3924	3.99	1852	1.1286	0.6656	0.6575	0.6554	0.6556

Framework versions

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