Hinglish Finetuned

🚀 hinglish-finetuned

This is a fine - tuned model based on verloop/Hinglish-Bert. It's trained on an unknown dataset and achieves a loss of 2.0786 on the evaluation set.

🚀 Quick Start

This model can be used right after fine - tuning. You can load it using relevant libraries and start making inferences.

✨ Features

• It is a fine - tuned version of verloop/Hinglish-Bert, potentially having better performance on specific tasks.
• It provides evaluation results on the evaluation set, with a loss of 2.0786.

📦 Installation

No specific installation steps are provided in the original document.

📚 Documentation

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: 2e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 25
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.18.0
• Pytorch 1.10.0+cu111
• Datasets 2.1.0
• Tokenizers 0.12.1