Abhi964 / IndicBERT_Finetuned_Final

huggingface.co
Total runs: 13
24-hour runs: 0
7-day runs: -4
30-day runs: -2
Model's Last Updated: July 05 2024
text-classification

Introduction of IndicBERT_Finetuned_Final

Model Details of IndicBERT_Finetuned_Final

IndicBERT_Finetuned_Final

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: 0.6539
  • Accuracy: 0.7227
  • Precision: 0.7377
  • Recall: 0.7227
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: 5e-05
  • train_batch_size: 64
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5
Training results
Training Loss Epoch Step Validation Loss Accuracy Precision Recall
0.8979 1.0 190 0.9064 0.5493 0.3712 0.5493
0.807 2.0 380 0.7564 0.65 0.6417 0.65
0.6731 3.0 570 0.6962 0.6833 0.7411 0.6833
0.6579 4.0 760 0.6723 0.6987 0.7213 0.6987
0.5946 5.0 950 0.6539 0.7227 0.7377 0.7227
Framework versions
  • Transformers 4.41.2
  • Pytorch 2.1.2
  • Datasets 2.19.2
  • Tokenizers 0.19.1

Runs of Abhi964 IndicBERT_Finetuned_Final on huggingface.co

13
Total runs
0
24-hour runs
1
3-day runs
-4
7-day runs
-2
30-day runs

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IndicBERT_Finetuned_Final huggingface.co is an AI model on huggingface.co that provides IndicBERT_Finetuned_Final's model effect (), which can be used instantly with this Abhi964 IndicBERT_Finetuned_Final model. huggingface.co supports a free trial of the IndicBERT_Finetuned_Final model, and also provides paid use of the IndicBERT_Finetuned_Final. Support call IndicBERT_Finetuned_Final model through api, including Node.js, Python, http.

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IndicBERT_Finetuned_Final install

IndicBERT_Finetuned_Final is an open source model from GitHub that offers a free installation service, and any user can find IndicBERT_Finetuned_Final on GitHub to install. At the same time, huggingface.co provides the effect of IndicBERT_Finetuned_Final install, users can directly use IndicBERT_Finetuned_Final installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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