Update README.md

README.md

@@ -8,7 +8,7 @@ pipeline_tag: text-generation
 tags:
 - table
 ---
-# Model Card for Model ID
+# Model Card for TAMA-5e-7
 
 <!-- Provide a quick summary of what the model is/does. -->
 
@@ -16,7 +16,7 @@ Recent advances in table understanding have focused on instruction-tuning large
 
 Through systematic analysis, we show that hyperparameters, such as learning rate, can significantly influence both table-specific and general capabilities. Contrary to the previous table instruction-tuning work, we demonstrate that smaller learning rates and fewer training instances can enhance table understanding while preserving general capabilities. Based on our findings, we introduce TAMA, a TAble LLM instruction-tuned from LLaMA 3.1 8B Instruct, which achieves performance on par with, or surpassing GPT-3.5 and GPT-4 on table tasks, while maintaining strong out-of-domain generalization and general capabilities. Our findings highlight the potential for reduced data annotation costs and more efficient model development through careful hyperparameter selection.
 
-## Model Details
+## 🚀 Model Details
 
 ### Model Description
 
@@ -42,7 +42,7 @@ Through systematic analysis, we show that hyperparameters, such as learning rate
 TAMA is intended for the use in table understanding tasks and to facilitate future research.
 
 
-## How to Get Started with the Model
+## 🔨 How to Get Started with the Model
 
 Use the code below to get started with the model.
 Starting with `transformers >= 4.43.0` onward, you can run conversational inference using the Transformers pipeline abstraction or by leveraging the Auto classes with the generate() function.
@@ -109,7 +109,7 @@ llamafactory-cli train yamls/train.yaml
 - **Cutoff length:** 2048
 - **Learning rate**: 5e-7
 
-## Evaluation
+## 📝 Evaluation
 
 ### Results