peft safetensors unsloth generated_from_trainer base_model:unsloth/tinyllama-chat-bnb-4bit base_model:adapter:unsloth/tinyllama-chat-bnb-4bit license:apache-2.0 region:us
---
base_model: unsloth/tinyllama-chat-bnb-4bit
library_name: peft
license: apache-2.0
tags:
- unsloth
- generated_from_trainer
model-index:
- name: english-marathi-colloquial-translator
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# english-marathi-colloquial-translator

This model is a fine-tuned version of [unsloth/tinyllama-chat-bnb-4bit](https://huggingface.co/unsloth/tinyllama-chat-bnb-4bit) on the RutujaPatil29/marathi-model-dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 8.7797

## Model description
This model is designed to translate English sentences into Marathi with a focus on colloquial language, informal phrases, and slang. Unlike traditional translation models, it understands the nuances of everyday spoken Marathi.

## Intended uses & limitations<br>

✅ Handles casual and slang Marathi well <br>
✅ Understands sentence structure and context<br>
⚠️ May struggle with highly formal translations<br>
⚠️ Does not support code-mixing (Hinglish/Marathenglish) yet<br>

## Training and evaluation data

Dataset Sources:<br>
The model was fine-tuned on a custom dataset created from:<br>
1️⃣ Scraped articles & text from Marathi news websites (Loksatta, Sakal, Maharashtra Times)<br>
2️⃣ Manually annotated informal translations for better conversational accuracy<br>
3️⃣ Commonly used Marathi slang and spoken phrases<br>

Data Cleaning & Preprocessing:<br>
Removed formal literary phrases to retain conversational style<br>
Tokenized text using SentencePiece/BPE<br>
Aligned informal Marathi with English inputs<br>
Evaluation Metrics:<br>
BLEU Score – Measures translation accuracy<br>
Perplexity (PPL) – Checks model fluency<br>
Human Evaluation – Native Marathi speakers verified outputs<br>




### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.1568        | 2.0   | 2    | 8.7847          |
| 4.1558        | 4.0   | 4    | 8.7847          |
| 4.1567        | 6.0   | 6    | 8.7847          |
| 4.1563        | 8.0   | 8    | 8.7837          |
| 3.8778        | 10.0  | 10   | 8.7797          |


### Framework versions

- PEFT 0.14.0
- Transformers 4.48.3
- Pytorch 2.6.0+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0