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Abhi964/
Paraphrase_IndicBERTv2-MLM-Back-TLM_onfull_FT2

Name: Paraphrase_IndicBERTv2-MLM-Back-TLM_onfull_FT2
Rating: 2.5 (7 reviews)

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ai4bharat/IndicBERTv2-MLM-Back-TLM

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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

Abhi964/Paraphrase_IndicBERTv2-MLM-Back-TLM_onfull_FT2

Paraphrase_IndicBERTv2-MLM-Back-TLM_onfull_FT2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Abhi964/
Paraphrase_IndicBERTv2-MLM-Back-TLM_onfull_FT2