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README.md

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----
-library_name: transformers
-tags: []
----
 
-# Model Card for Model ID
+# llama-3.2-1B-MS-MARCO-qlora
 
-<!-- Provide a quick summary of what the model is/does. -->
+Este modelo es una versión afinada del modelo [meta-llama/Llama-3.2-1B](https://huggingface.co/meta-llama/Llama-3.2-1B) utilizando el conjunto de datos MS MARCO para tareas de generación de respuestas.
 
+## Descripción del Modelo
 
+- **Modelo Base:** meta-llama/Llama-3.2-1B
+- **Técnicas Utilizadas:**
+  - Quantization con QLoRA
+  - Afinación con LoRA y PEFT
+- **Arquitectura:**
+  - Parámetros entrenables: Solo los adaptadores LoRA
+  - Parámetros totales: 771819520
+  - Parámetros entrenables: 22544384
 
-## Model Details
+## Conjunto de Datos
 
-### Model Description
+- **Nombre del Conjunto de Datos:** MS MARCO
+- **Descripción:** Conjunto de datos de comprensión lectora a gran escala que incluye preguntas y respuestas reales de usuarios.
+- **Tamaño del Conjunto de Entrenamiento:** 56588
+- **Tamaño del Conjunto de Validación:** 14148
+- **Preprocesamiento:**
+  - Limpieza de texto
+  - Tokenización
+  - Creación de prompts combinando contexto, pregunta y respuesta
 
-<!-- Provide a longer summary of what this model is. -->
+## Entrenamiento
 
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+- **Hiperparámetros:**
+  - Número de épocas: 7
+  - Tamaño de lote de entrenamiento: 16
+  - Tamaño de lote de evaluación: 8
+  - Tasa de aprendizaje: 0.0002
+- **Configuración de LoRA:**
+  - r (rango): 32
+  - lora_alpha: 32
+  - lora_dropout: 0.05
+- **Recursos Computacionales:**
+  - Dispositivo: cuda
+  - Memoria GPU utilizada: Dependiente del hardware
 
-- **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]
+## Resultados
 
-### Model Sources [optional]
+### Métricas
 
-<!-- Provide the basic links for the model. -->
+- **Pérdida de Entrenamiento Final:** 0.5787
+- **Pérdida de Validación Final:** 2.6848
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+### Gráficas
 
-## Uses
+![Curva de Pérdida](./loss_curve.png)
 
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+## Uso del Modelo
 
-### Direct Use
+Para utilizar este modelo, puedes cargarlo de la siguiente manera:
 
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
 
-[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
-
-### 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]
+model = AutoModelForCausalLM.from_pretrained('TheBug95/llama-3.2-1B-MS-MARCO-qlora')
+tokenizer = AutoTokenizer.from_pretrained('TheBug95/llama-3.2-1B-MS-MARCO-qlora')