Update README.md

README.md

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 license: apache-2.0
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-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
-This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
+# Model Card for PaliGemma Dermatology Model
 
 ## Model Details
 
 ### Model Description
 
-<!-- Provide a longer summary of what this model is. -->
-
+This model, based on the PaliGemma-3B architecture, has been fine-tuned for dermatology-related image and text processing tasks. The model is designed to assist in the identification of various skin conditions using a combination of image analysis and natural language processing.
 
 
 - **Developed by:** Bruce_Wayne
 - **Funded by [optional]:** Jhonny and koti
 - **Model type:** vision model
 - **Finetuned from model [optional]:** https://huggingface.co/google/paligemma-3b-pt-224
-
+- **LoRa Adaptors used:** Yes
+- **Intended use:** Medical image analysis, specifically for dermatology
+**
 ## 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. -->
-
 ### Direct Use
 
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+The model can be directly used for analyzing dermatology images, providing insights into potential skin conditions.
 
-[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]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
 
 ## 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. -->
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-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+**Skin Tone Bias:** The model may have been trained on a dataset that does not adequately represent all skin tones, potentially leading to biased results.
+**Geographic Bias:** The model's performance may vary depending on the prevalence of certain conditions in different geographic regions.
 
 ## How to Get Started with the Model
 
-Use the code below to get started with the model.
+** python 
 
-[More Information Needed]
+from transformers import AutoProcessor, PaliGemmaForConditionalGeneration
 
+model_id = "brucewayne0459/paligemma_derm"
+processor = AutoProcessor.from_pretrained(model_id)
+model = PaliGemmaForConditionalGeneration.from_pretrained(model_id)
+**
 ## 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]
+The model was fine-tuned on a dataset of dermatological images combined with disease names
 
 ### 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]
-
+The model was fine-tuned using LoRA (Low-Rank Adaptation) for more efficient training. Mixed precision (bfloat16) was used to speed up training and reduce memory usage.
 
 #### 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 -->
+- **Training regime:** Mixed precision (bfloat16)
+- **Epochs:** 10
+- **Learning rate:** 2e-5
+- **Batch size:** 6
+- **Gradient accumulation steps:** 4
 
-#### 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. -->
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 ### 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]
+The model was evaluated on a separate validation set of dermatological images and Disease Names, distinct from the training data.
 
 #### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
+- **Validation Loss:** The loss was tracked throughout the training process to evaluate model performance.
+- **Accuracy:** The primary metric for assessing model predictions.
 ### Results
 
-[More Information Needed]
+The model achieved a final validation loss of approximately 0.2214, indicating reasonable performance in predicting skin conditions based on the dataset used.
 
 #### 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]
+- **Hardware Type:** 1 x L4 GPU
+- **Hours used:** ~22 HOURS
+- **Cloud Provider:** LIGHTNING AI
+- **Compute Region:** USA
+- **Carbon Emitted:** 0.9 kg eq. CO2
 
-## Technical Specifications [optional]
+## Technical Specifications
 
 ### Model Architecture and Objective
 
-[More Information Needed]
+- **Architecture:** Vision-Language model based on PaliGemma-3B
+- **Objective:** To classify and diagnose dermatological conditions from images and text
 
 ### Compute Infrastructure
 
-[More Information Needed]
-
 #### Hardware
 
-[More Information Needed]
-
-#### 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]
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-## More Information [optional]
-
-[More Information Needed]
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-## Model Card Authors [optional]
-
-[More Information Needed]
-
-## Model Card Contact
-
-[More Information Needed]
+- **GPU:** 1xL4 GPU
+- 
+## Model Card Authors 
+Bruce_Wayne