Update README.md

README.md

@@ -12,7 +12,7 @@ widget:
 ---
 
 
-# Model Card for Model ID
+# BART (large-sized model), fine-tuned on synthetic_text_to_sql
 
 Generate SQL from Natural Language question with a SQL context.
 
@@ -30,98 +30,66 @@ BART from facebook/bart-large-cnn is fintuned on gretelai/synthetic_text_to_sql
 - **Finetuned from model [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn?text=The+tower+is+324+metres+%281%2C063+ft%29+tall%2C+about+the+same+height+as+an+81-storey+building%2C+and+the+tallest+structure+in+Paris.+Its+base+is+square%2C+measuring+125+metres+%28410+ft%29+on+each+side.+During+its+construction%2C+the+Eiffel+Tower+surpassed+the+Washington+Monument+to+become+the+tallest+man-made+structure+in+the+world%2C+a+title+it+held+for+41+years+until+the+Chrysler+Building+in+New+York+City+was+finished+in+1930.+It+was+the+first+structure+to+reach+a+height+of+300+metres.+Due+to+the+addition+of+a+broadcasting+aerial+at+the+top+of+the+tower+in+1957%2C+it+is+now+taller+than+the+Chrysler+Building+by+5.2+metres+%2817+ft%29.+Excluding+transmitters%2C+the+Eiffel+Tower+is+the+second+tallest+free-standing+structure+in+France+after+the+Millau+Viaduct.)**
 - **Dataset:** [gretelai/synthetic_text_to_sql](https://huggingface.co/datasets/gretelai/synthetic_text_to_sql)
 
-## Uses
+## Intended uses & limitations
 
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+Addressing the power of LLM in fintuned downstream task. Implemented as a personal Project.
 
-### Direct Use
+### How to use
 
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+# Load model directly
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
-[More Information Needed]
+tokenizer = AutoTokenizer.from_pretrained("SwastikM/bart-large-nl2sql")
 
-### Downstream Use [optional]
+model = AutoModelForSeq2SeqLM.from_pretrained("SwastikM/bart-large-nl2sql")
 
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+query_question_with_context = "sql_prompt: Which economic diversification efforts in the 'diversification' table have a higher budget than the average budget for all economic diversification efforts in the 'budget' table? sql_context: CREATE TABLE diversification (id INT, effort VARCHAR(50), budget FLOAT); CREATE TABLE budget (diversification_id INT, diversification_effort VARCHAR(50), amount FLOAT);"
 
-[More Information Needed]
+sql = model.generate(text)
 
+print(sql)
 
-## How to Get Started with the Model
 
-Use the code below to get started with the model.
-
-[More Information Needed]
 
 ## Training Details
 
 ### Training Data
 
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+[gretelai/synthetic_text_to_sql](https://huggingface.co/datasets/gretelai/synthetic_text_to_sql)
 
 [More Information Needed]
 
 ### Training Procedure
 
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+HuggingFace Accelerate with Training Loop.
 
-#### Preprocessing [optional]
+#### Preprocessing 
 
-[More Information Needed]
+- ***Encoder Input:*** "sql_prompt: " + data['sql_prompt']+" sql_context: "+data['sql_context']
+- ***Decoder Input:*** data['sql']
 
 
 #### Training Hyperparameters
 
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+- **Optimizer:** AdamW
+- **lr:** 2e-5
+- **decay:** linear
+- **num_warmup_steps:** 0
+- **batch_size:** 8
+- **num_training_steps:** 12500
 
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
 
 ## Evaluation
 
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
-### Results
-
-[More Information Needed]
-
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
-
-[More Information Needed]
+***Rouge Score***
+- **Rouge1:** 55.69
+- **Rouge2:** 42.99
+- **RougeL:** 51.43
+- **RougeLsum:** 51.40
 
 #### Hardware
 
-[More Information Needed]
+-**GPU:** P100
 
 
 ## Citation
@@ -162,6 +130,6 @@ Use the code below to get started with the model.
 }
 
 
-## Model Card Authors [optional]
+## Model Card Authors
 
-[Swastik Maiti]
+Swastik Maiti