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Llama-3.2-1B-finetuned-generalQA-peft-4bit

Text Generation

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Chryslerx10 commited on Oct 9, 2024

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@@ -3,197 +3,58 @@ library_name: transformers
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-# Model Card for Model ID
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-## Model Details
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-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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 tags: []
 ---
+## Model Description
+Llama-3.2-1B-finetuned-generalQA-peft-4bit is a fine-tuned version of the Llama-3.2-1B model, specialized for general question-answering tasks. The model has been fine-tuned using Low-Rank Adaptation (LoRA) with 4-bit quantization, making it efficient for deployment on resource-constrained hardware.
+Model Architecture
+    Base Model: Llama-3.2-1B
+    Parameters: Approximately 1 Billion
+    Quantization: 4-bit using the bitsandbytes library
+    Fine-tuning Method: PEFT with LoRA
+## Training Data
+The model was fine-tuned on the Databricks Dolly 15k Subset for General QA dataset. This dataset is a subset focusing on general question-answering tasks, derived from the larger Databricks Dolly 15k dataset.
 ### Training Procedure
+    Fine-tuning Configuration:
+        LoRA Rank (r): 8
+        LoRA Alpha: 16
+        LoRA Dropout: 0.5
+        Number of Epochs: 30
+        Batch Size: 2 (per device)
+        Learning Rate: 2e-5
+        Evaluation Strategy: Evaluated at each epoch
+        Optimizer: AdamW
+        Mixed Precision: FP16
+    Hardware Used: [Specify hardware if known, e.g., "Single NVIDIA A100 GPU"]
+    Libraries:
+        transformers
+        datasets
+        peft
+        bitsandbytes
+        trl
+        evaluate
+## Intended Use
+The model is intended for generating informative answers to general questions. It can be integrated into applications such as chatbots, virtual assistants, educational tools, and information retrieval systems.
+## Limitations and Biases
+    Knowledge Cutoff: The model's knowledge is limited to the data it was trained on. It may not have information on events or developments that occurred after the dataset was created.
+    Accuracy: While the model strives to provide accurate answers, it may occasionally produce incorrect or nonsensical responses. Always verify critical information from reliable sources.
+    Biases: The model may inherit biases present in the training data. Users should be cautious and critically evaluate the model's outputs, especially in sensitive contexts.
+## Acknowledgements
+  Base Model: <a href="https://huggingface.co/meta-llama/Llama-3.2-1B">Meta AI's Llama-3.2-1B </a>
+  Dataset: <a href="https://huggingface.co/datasets/bergr7f/databricks-dolly-15k-subset-general_qa">Databricks Dolly 15k Subset for General QA</a>
+  Libraries Used:
+      Transformers
+      PEFT
+      TRL
+      BitsAndBytes