metadata

license: mit
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: indic-bert-finetuned-non-code-mixed-DS
    results: []

indic-bert-finetuned-non-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: 0.9997
Accuracy: 0.5620
Precision: 0.5591
Recall: 0.5203
F1: 0.5078

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: 32
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
1.0673	3.99	926	1.0361	0.4142	0.4092	0.3851	0.2750
1.0144	7.98	1852	1.0147	0.5146	0.5851	0.4714	0.4184
0.9882	11.97	2778	1.0045	0.5599	0.5728	0.5191	0.5047
0.9699	15.97	3704	1.0004	0.5642	0.5620	0.5264	0.5193
0.9591	19.96	4630	0.9997	0.5620	0.5591	0.5203	0.5078

Framework versions

Transformers 4.20.1
Pytorch 1.10.1+cu111
Datasets 2.3.2
Tokenizers 0.12.1