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Ionio-ai/
fine-tuned-PL_BERT-hindi

Name: fine-tuned-PL_BERT-hindi
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PL-BERT Fine-Tuned on Hindi Wikipedia Dataset

This model is a fine-tuned version of PL-BERT, specifically trained on the Hindi subset of the Wiki40b dataset. The model has been optimized to understand and generate high-quality Hindi text, making it suitable for various NLP tasks in the Hindi language. For more information about this model, check out the GitHub repository.

Model Overview

Model Name: PL-BERT (Fine-tuned on Hindi)
Base Model: PL-BERT (Multilingual BERT variant)
Dataset: Hindi subset from Wiki40b (51,000 cleaned Wikipedia articles)
Precision: Mixed precision (FP16)

The fine-tuning process focused on improving the model's ability to handle Hindi text more effectively by leveraging a large, cleaned corpus of Wikipedia articles in Hindi.

Training Details

Model: PL-BERT
Dataset: Hindi subset from Wiki40b
Batch Size: 64
Mixed Precision: FP16
Optimizer: AdamW
Training Steps: 15,000

Training Progress

Final Loss: 1.879
Vocabulary Loss: 0.49
Token Loss: 1.465

Validation Results

During training, we monitored performance with validation metrics:

Validation Loss: 1.879
Vocabulary Accuracy: 78.54%
Token Accuracy: 82.30%

Ionio-ai/fine-tuned-PL_BERT-hindi