indic-bert-finetuned-code-mixed-DS

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

• Loss: 0.8647
• Accuracy: 0.5795
• Precision: 0.5485
• Recall: 0.5287
• F1: 0.4391

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: 1e-06
• 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: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
1.0937	2.0	497	1.0813	0.3602	0.3587	0.4257	0.2834
1.0189	3.99	994	0.9482	0.5493	0.3887	0.5246	0.4080
0.9208	5.99	1491	0.9002	0.5714	0.3813	0.5292	0.4170
0.8803	7.98	1988	0.8758	0.5654	0.3889	0.5300	0.4159
0.8482	9.98	2485	0.8657	0.5795	0.3867	0.5365	0.4228
0.8293	11.98	2982	0.8734	0.5835	0.3796	0.5298	0.4214
0.8131	13.97	3479	0.8567	0.5835	0.5018	0.5414	0.4350
0.8	15.97	3976	0.8547	0.5835	0.5610	0.5460	0.4361
0.7933	17.96	4473	0.8650	0.5775	0.5317	0.5252	0.4373
0.7835	19.96	4970	0.8647	0.5795	0.5485	0.5287	0.4391

Framework versions

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