hing-mbert-finetuned-combined-DS

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

• Loss: 1.4833
• Accuracy: 0.6721
• Precision: 0.6460
• Recall: 0.6443
• F1: 0.6447

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
0.7382	2.0	1423	0.8027	0.6749	0.6544	0.6590	0.6538
0.2943	4.0	2846	1.4833	0.6721	0.6460	0.6443	0.6447

Framework versions

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