Paraphrase_IndicBERTv2-MLM-Back-TLM_onfull_FT2

This model is a fine-tuned version of ai4bharat/IndicBERTv2-MLM-Back-TLM on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.6694
• Accuracy: 0.872
• F1: 0.8716

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: 2.448092452817481e-05
• train_batch_size: 16
• eval_batch_size: 64
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.3163	1.0	313	0.3615	0.8485	0.8472
0.2652	2.0	626	0.3545	0.867	0.8668
0.1021	3.0	939	0.4961	0.864	0.8638
0.0294	4.0	1252	0.6694	0.872	0.8716
0.0941	5.0	1565	0.7800	0.8665	0.8664
0.058	6.0	1878	0.8815	0.8645	0.8641
0.0002	7.0	2191	0.8727	0.8655	0.8654
0.004	8.0	2504	0.9035	0.8655	0.8653

Framework versions

• Transformers 4.49.0
• Pytorch 2.6.0+cu124
• Datasets 3.3.2
• Tokenizers 0.21.0