
This is the WMT 2023 shared task dataset for fine-tuning meta-llama/Llama-2-13b-chat-hf model. 
We have concatenated and shuffled En-Gu, Hi, Mr, Ta, Te data from both training and validation sets. We have excluded approx. > 10 sample prompts for in-context learning scenario with test set. 
Our sample prompt is:
```
<s>[INST] <<SYS>> You are a quality estimation model which accuractely predicts the translation quality as mean z_score. For perfectly meaningful translation, predict high z_score and for a meaningless or erroneous translation predict low z_score. Penalize the z_score on translation errors within [TGT] based on source sentence in [SRC]. Do not consider any other exisiting translation evaluation metrics. <</SYS>> For the following translation from English to Marathi, [SRC] Mudiyettu performers purify themselves through fasting and prayer, then draw a huge image of goddess Kali, called as kalam, on the temple floor with coloured powders, wherein the spirit of the goddess is invoked. [/SRC][TGT] मुडियेट्टु कलाकार उपवास आणि प्रार्थनेद्वारे स्वतःला शुद्ध करतात, त्यानंतर मंदिराच्या मजल्यावर काळम नावाच्या देवीची मोठी प्रतिमा काढतात, ज्यात देवीच्या आत्म्याची प्रार्थना केली जाते. [/TGT], predict the z_score [/INST] z_score: -0.4986</s>
```
size_categories:10K<n<100K language:en language:hi language:mr language:gu language:ta language:te license:cc-by-nc-sa-4.0 quality estimation llama-2-format instruction tuning wmt 2023 data region:us
{"language": ["en", "hi", "mr", "gu", "ta", "te"], "license": "cc-by-nc-sa-4.0", "size_categories": ["10K<n<100K"], "tags": ["quality estimation", "llama-2-format", "instruction tuning", "wmt 2023 data"]}
TAGS
#size_categories-10K<n<100K #language-English #language-Hindi #language-Marathi #language-Gujarati #language-Tamil #language-Telugu #license-cc-by-nc-sa-4.0 #quality estimation #llama-2-format #instruction tuning #wmt 2023 data #region-us 


This is the WMT 2023 shared task dataset for fine-tuning meta-llama/Llama-2-13b-chat-hf model. 
We have concatenated and shuffled En-Gu, Hi, Mr, Ta, Te data from both training and validation sets. We have excluded approx. > 10 sample prompts for in-context learning scenario with test set. 
Our sample prompt is:

TAGS
#size_categories-10K<n<100K #language-English #language-Hindi #language-Marathi #language-Gujarati #language-Tamil #language-Telugu #license-cc-by-nc-sa-4.0 #quality estimation #llama-2-format #instruction tuning #wmt 2023 data #region-us 

passage: TAGS
#size_categories-10K<n<100K #language-English #language-Hindi #language-Marathi #language-Gujarati #language-Tamil #language-Telugu #license-cc-by-nc-sa-4.0 #quality estimation #llama-2-format #instruction tuning #wmt 2023 data #region-us 
