hing-roberta-finetuned-TRAC-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: 1.1610
• Accuracy: 0.7149
• Precision: 0.6921
• Recall: 0.6946
• F1: 0.6932

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: 4.8796394086479776e-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: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.7229	2.0	1224	0.7178	0.6928	0.6815	0.6990	0.6780
0.3258	3.99	2448	1.1610	0.7149	0.6921	0.6946	0.6932

Framework versions

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