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README.md

@@ -1,117 +1,207 @@
 ---
-language:
-- en
-license: llama3.2
+base_model: meta-llama/Llama-3.2-1B-Instruct
+library_name: peft
+pipeline_tag: text-generation
 tags:
-- summarization
-- llama
+- base_model:adapter:meta-llama/Llama-3.2-1B-Instruct
 - lora
-- xsum
-datasets:
-- xsum
-metrics:
-- rouge
-library_name: transformers
-pipeline_tag: summarization
+- transformers
 ---
 
-# LLaMA 3.2 1B Instruct - XSum Summarization (LoRA)
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
 
-This model is a LoRA fine-tuned version of [`meta-llama/Llama-3.2-1B-Instruct`](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct) for extreme summarization on the XSum dataset.
 
 ## Model Details
 
-- **Base Model**: meta-llama/Llama-3.2-1B-Instruct
-- **Method**: LoRA (Low-Rank Adaptation)
-- **Task**: Instruction-based summarization
-- **Dataset**: XSum (extreme summarization)
-- **Training Samples**: 5,000
-- **Validation Samples**: 500
-
-## Training Configuration
-
-### LoRA Parameters
-- **Rank (r)**: 16
-- **Alpha**: 32
-- **Dropout**: 0.05
-- **Target Modules**: q_proj, k_proj, v_proj...
-
-### Training Hyperparameters
-- **Epochs**: 3
-- **Batch Size**: 4
-- **Gradient Accumulation**: 4
-- **Learning Rate**: 0.0002
-- **Optimizer**: paged_adamw_8bit
-- **Scheduler**: cosine
-- **Quantization**: 4-bit (nf4)
-
-## Performance
-
-Evaluated on 200 validation samples:
-
-| Metric | Score |
-|--------|-------|
-| ROUGE-1 | 0.2077 |
-| ROUGE-2 | 0.0637 |
-| ROUGE-L | 0.1519 |
-| ROUGE-Lsum | 0.1566 |
-
-## Usage
-
-```python
-from transformers import AutoTokenizer, AutoModelForCausalLM
-from peft import PeftModel
-import torch
-
-# Load base model
-model_name = "meta-llama/Llama-3.2-1B-Instruct"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(
-    model_name,
-    torch_dtype=torch.float16,
-    device_map="auto"
-)
-
-# Load LoRA adapters
-model = PeftModel.from_pretrained(model, "Deepu1965/xsum-llama1b-instruct-lora")
-
-# Prepare input
-document = "Your news article here..."
-prompt = (
-    "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\n"
-    "You are a helpful assistant that summarizes news articles into one concise sentence.\n"
-    "<|eot_id|><|start_header_id|>user<|end_header_id|>\n\n"
-    f"Summarize this article in one sentence:\n\n{document}\n"
-    "<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n"
-)
-
-inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
-outputs = model.generate(**inputs, max_new_tokens=128)
-summary = tokenizer.decode(outputs[0], skip_special_tokens=True)
-```
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **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]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## 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. -->
+
+[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. -->
+
+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
 
-- **Framework**: HuggingFace Transformers + PEFT
-- **Quantization**: bitsandbytes 4-bit
-- **Gradient Checkpointing**: Enabled
-- **Mixed Precision**: FP16
-
-## Limitations
-
-- Trained on English news articles only
-- Optimized for single-sentence summaries
-- May not generalize well to other domains
-- Requires LoRA adapters loaded on top of base model
-
-## Citation
-
-```bibtex
-@misc{llama32-xsum-lora,
-  author = {Your Name},
-  title = {LLaMA 3.2 1B XSum LoRA},
-  year = {2025},
-  publisher = {HuggingFace},
-  url = {https://huggingface.co/Deepu1965/xsum-llama1b-instruct-lora}
-}
-```
+### 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]
+
+### 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]
+
+## 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]
+
+#### 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]
+
+### 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]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.17.1

adapter_config.json

@@ -25,13 +25,13 @@
   "rank_pattern": {},
   "revision": null,
   "target_modules": [
-    "q_proj",
+    "up_proj",
     "k_proj",
-    "gate_proj",
     "down_proj",
-    "up_proj",
-    "v_proj",
-    "o_proj"
+    "gate_proj",
+    "q_proj",
+    "o_proj",
+    "v_proj"
   ],
   "target_parameters": null,
   "task_type": "CAUSAL_LM",

adapter_model.safetensors

@@ -1,3 +1,3 @@
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