Update README.md

README.md

@@ -1,202 +1,130 @@
 ---
 base_model: llava-hf/llava-v1.6-mistral-7b-hf
 library_name: peft
+license: apache-2.0
+datasets:
+- mirzaei2114/stackoverflowVQA-filtered-small
+language:
+- en
+tags:
+- llava
+- llava-next
+- fine-tuned
+- stack-overflow
+- qlora
+- images
+- vqa
+- 4bit
 ---
 
 # Model Card for Model ID
 
-<!-- Provide a quick summary of what the model is/does. -->
-
-
+Finetuned LLaVA-Next model for Visual QA on Stack Overflow questions with images.
 
 ## Model Details
 
 ### Model Description
 
-<!-- Provide a longer summary of what this model is. -->
+This model is a finetuned version of **LLaVA-Next (llava-hf/llava-v1.6-mistral-7b-hf)** specifically for visual question answering (VQA)
+on Stack Overflow questions containing images. The model was finetuned using **QLoRA** with 4-bit quantization, optimized to handle both
+text and image inputs.
 
+The training dataset was filtered from the **mirzaei2114/stackoverflowVQA-filtered-small** dataset.
+Only samples with a maximum input length of 1024 (for both question and answer combined) were used. Images were kept
+to size to capture detail needed for methods such as optical character recognition.
 
 
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
 
-### Model Sources [optional]
+- **Developed by:** Adam Cassidy
+- **Model type:** Visual QA
+- **Language(s) (NLP):** EN
+- **License:** Apache License, Version 2.0
+- **Finetuned from model [optional]:** llava-hf/llava-v1.6-mistral-7b-hf
 
-<!-- Provide the basic links for the model. -->
+### Model Sources
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Repository:** [llava-hf/llava-v1.6-mistral-7b-hf](https://huggingface.co/llava-hf/llava-v1.6-mistral-7b-hf)
 
 ## Uses
 
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+Drag a snipping rectangle for a screenshot around the exact focus/context for a question related to software development(usually front end)
+and accompany it with the question for inference.
 
 ### Direct Use
 
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
+Visual Question Answering (VQA) on technical Stack Overflow (software-adjacent) questions with accompanying images.
 
 ### Out-of-Scope Use
 
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
+General-purpose VQA tasks, though performance on non-technical domains may vary.
 
 ## Bias, Risks, and Limitations
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
-
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+Model Capacity: The model was trained using 4-bit QLoRA.
+Dataset Size: The training dataset is relatively small, and this may impact generalization to other VQA datasets or domains outside of Stack Overflow.
 
 ## How to Get Started with the Model
 
-Use the code below to get started with the model.
-
-[More Information Needed]
+To use this model, ensure you have the following dependencies installed:
+torch==2.4.1+cu121
+transformers==4.45.1
 
 ## 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. -->
-
-[More Information Needed]
+[mirzaei2114/stackoverflowVQA-filtered-small](https://huggingface.co/datasets/mirzaei2114/stackoverflowVQA-filtered-small/viewer/default/train)
 
 ### Training Procedure
 
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-
-#### Preprocessing [optional]
-
-[More Information Needed]
-
-
 #### 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 -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
+  TrainingArguments(
+      per_device_train_batch_size=4,
+      per_device_eval_batch_size=4,
+      max_grad_norm=0.1,
+      evaluation_strategy="steps",
+      eval_steps=15,
+      group_by_length=True,
+      logging_steps=15,
+      gradient_checkpointing=True,
+      gradient_accumulation_steps=2,
+      num_train_epochs=3,
+      weight_decay=0.1,
+      warmup_steps=10,
+      lr_scheduler_type="cosine",
+      learning_rate=1e-5,
+      save_steps=15,
+      save_total_limit=5,
+      bf16=True,
+      remove_unused_columns=False
+  )
+
+#### Speeds, Sizes, Times
+
+checkpoint-240
 
 ## Evaluation
 
-<!-- This section describes the evaluation protocols and provides the results. -->
+Evaluation Loss (Pre-finetuning): 2.93
+Validation Loss (Post-finetuning): 1.78
 
 ### 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]
-
-#### Summary
-
-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
+[mirzaei2114/stackoverflowVQA-filtered-small](https://huggingface.co/datasets/mirzaei2114/stackoverflowVQA-filtered-small/viewer/default/test)
 
 ### Compute Infrastructure
 
-[More Information Needed]
-
 #### Hardware
 
-[More Information Needed]
+L4 GPU
 
 #### Software
 
-[More Information Needed]
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Model Card Authors [optional]
-
-[More Information Needed]
-
-## Model Card Contact
+Google Colab
 
-[More Information Needed]
 ### Framework versions
 
 - PEFT 0.13.1.dev0