IIIT-L / hing-roberta-finetuned-TRAC-DS

huggingface.co
Total runs: 13
24-hour runs: 0
7-day runs: -1
30-day runs: 6
Model's Last Updated: September 10 2022
text-classification

Introduction of hing-roberta-finetuned-TRAC-DS

Model Details of hing-roberta-finetuned-TRAC-DS

hing-roberta-finetuned-TRAC-DS

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

  • Loss: 1.1610
  • Accuracy: 0.7149
  • Precision: 0.6921
  • Recall: 0.6946
  • F1: 0.6932
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
0.7229 2.0 1224 0.7178 0.6928 0.6815 0.6990 0.6780
0.3258 3.99 2448 1.1610 0.7149 0.6921 0.6946 0.6932
Framework versions
  • Transformers 4.20.1
  • Pytorch 1.10.1+cu111
  • Datasets 2.3.2
  • Tokenizers 0.12.1

Runs of IIIT-L hing-roberta-finetuned-TRAC-DS on huggingface.co

13
Total runs
0
24-hour runs
0
3-day runs
-1
7-day runs
6
30-day runs

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