sinem02
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Qwen2.5-Coder-1.5B-LoRA-Deep-v2

@@ -15,7 +15,7 @@ tags:
 # Model Card for Qwen2.5-1.5B-Coder-Finetune
-This model is a fine-tuned version of [Qwen/Qwen2.5-Coder-1.5B](https://huggingface.co/Qwen/Qwen2.5-Coder-1.5B) aimed at improving coding capabilities and reasoning traces. It was trained using the **Naholav/CodeGen-Diverse-5K** dataset with a focus on structured reasoning using `<think>` tags.
 ## Model Details
@@ -40,190 +40,4 @@ Input: [Your Problem Description]
 <think>
 [Model generates reasoning here]
 </think>
-Solution: [Model generates code here]
-## 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. -->
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-### Downstream Use [optional]
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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-### Out-of-Scope Use
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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-## Bias, Risks, and Limitations
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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-### 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.
-## How to Get Started with the Model
-Use the code below to get started with the model.
-[More Information Needed]
-## Training Details
-### Training Data
-The model was trained on the Naholav/CodeGen-Diverse-5K dataset, which contains diverse coding problems and solutions formatted to encourage reasoning.
-[More Information Needed]
-### Training Procedure
-The model was fine-tuned using the following hyperparameters on a GPU setup:
-Learning Rate: 2e-4
-Optimizer: adamw_torch_fused
-Scheduler: Cosine decay with 0.03 warmup ratio
-Train Batch Size: 4 (per device)
-Gradient Accumulation Steps: 4
-Epochs: 3
-Precision: fp16 (Mixed Precision)
-Weight Decay: 0.01
-Max Gradient Norm: 0.3
-Gradient Checkpointing: Enabled to save memory
-#### 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. -->
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-## Evaluation
-<!-- This section describes the evaluation protocols and provides the results. -->
-### Testing Data, Factors & Metrics
-#### Testing Data
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-#### Factors
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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-#### Metrics
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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-### Results
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-#### 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
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-### Compute Infrastructure
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-#### Hardware
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-#### Software
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-## 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:**
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-**APA:**
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-## Glossary [optional]
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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-## More Information [optional]
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-## Model Card Authors [optional]
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-## Model Card Contact
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 # Model Card for Qwen2.5-1.5B-Coder-Finetune
+This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B](https://huggingface.co/Qwen/Qwen2.5-1.5B) aimed at improving coding capabilities and reasoning traces. It was trained using the **Naholav/CodeGen-Diverse-5K** dataset with a focus on structured reasoning using `<think>` tags.
 ## Model Details
 <think>
 [Model generates reasoning here]
 </think>
+Solution: [Model generates code here]