Update README.md

README.md

@@ -11,48 +11,40 @@ model-index:
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
+Certainly! Here's a Model Card for your Hugging Face model with the provided information in English:
 
-# core2
+---
+
+# Model Card: LLama 2 - Version 7b (Embedding + Output + 1 Hidden Layer)
 
-This model is a fine-tuned version of [./model](https://huggingface.co/./model) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 2.5063
-- Accuracy: 0.4398
+## Overview
 
-## Model description
+- **Link to Training Progress:** [WandB Training Progress](https://wandb.ai/inteligenciaartificialcursos/huggingface/runs/wjh9m9x1/workspace?workspace=user-inteligenciaartificialcursos)
 
-More information needed
+- **Model Name:** LLama 2 - Version 7b
 
-## Intended uses & limitations
+- **Total Parameters:** 446 million
 
-More information needed
+## Training Data
 
-## Training and evaluation data
+The model has been trained with the following sequence of datasets:
 
-More information needed
+1. **GPT-2 Data (In Progress):** The initial training phase involves GPT-2 data and is currently in the finalization stage.
 
-## Training procedure
+2. **Wikipedia QA in Markdown (Next Stage):** The model's training will continue with Wikipedia question-answering data in Markdown format.
 
-### Training hyperparameters
+3. **QA with Rhetoric (Future Stages):** The model will further be fine-tuned with question-answering data generated from various LLama models, incorporating rhetorical elements.
 
-The following hyperparameters were used during training:
-- learning_rate: 0.0005
-- train_batch_size: 1
-- eval_batch_size: 8
-- seed: 42
-- gradient_accumulation_steps: 32
-- total_train_batch_size: 32
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- num_epochs: 2.0
+## Model Description
 
-### Training results
+The LLama 2 - Version 7b model is a powerful language model with a total of 446 million parameters. It utilizes embeddings, an output layer, and one hidden layer to perform a wide range of natural language processing tasks. The training is conducted in multiple stages, each focused on different datasets and objectives.
 
+## Disclaimer
 
+This model card provides an overview of the LLama 2 - Version 7b model, its training data, and intended use cases. Keep in mind that the model's performance may vary depending on the specific task or dataset. Users are encouraged to evaluate the model's suitability for their applications and exercise caution when using it in real-world scenarios.
 
-### Framework versions
+For any further inquiries or issues related to this model, please contact the model developers through the provided training progress link.
+
+---
 
-- Transformers 4.34.0.dev0
-- Pytorch 2.0.1+cu117
-- Datasets 2.14.5
-- Tokenizers 0.13.3
+Feel free to customize this Model Card further if you have additional details or specific use cases you'd like to highlight.