docs: training considerations for small models to the documentation

docs/en/concepts/training.mdx

@@ -65,3 +65,67 @@ Remember to regularly update and retrain your agents to ensure they stay up-to-d
 
 Happy training with CrewAI! 🚀
 
+## Small Language Model Considerations
+
+<Warning>
+  When using smaller language models (≤7B parameters) for training data evaluation, be aware that they may face challenges with generating structured outputs and following complex instructions.
+</Warning>
+
+### Limitations of Small Models in Training Evaluation
+
+<CardGroup cols={2}>
+  <Card title="JSON Output Accuracy" icon="triangle-exclamation">
+    Smaller models often struggle with producing valid JSON responses needed for structured training evaluations, leading to parsing errors and incomplete data.
+  </Card>
+  <Card title="Evaluation Quality" icon="chart-line">
+    Models under 7B parameters may provide less nuanced evaluations with limited reasoning depth compared to larger models.
+  </Card>
+  <Card title="Instruction Following" icon="list-check">
+    Complex training evaluation criteria may not be fully followed or considered by smaller models.
+  </Card>
+  <Card title="Consistency" icon="rotate">
+    Evaluations across multiple training iterations may lack consistency with smaller models.
+  </Card>
+</CardGroup>
+
+### Recommendations for Training
+
+<Tabs>
+  <Tab title="Best Practice">
+    For optimal training quality and reliable evaluations, we strongly recommend using models with at least 7B parameters or larger:
+
+    ```python
+    from crewai import Agent, Crew, Task, LLM
+
+    # Recommended minimum for training evaluation
+    llm = LLM(model="mistral/open-mistral-7b")
+
+    # Better options for reliable training evaluation
+    llm = LLM(model="anthropic/claude-3-sonnet-20240229-v1:0")
+    llm = LLM(model="gpt-4o")
+
+    # Use this LLM with your agents
+    agent = Agent(
+        role="Training Evaluator",
+        goal="Provide accurate training feedback",
+        llm=llm
+    )
+    ```
+
+    <Tip>
+      More powerful models provide higher quality feedback with better reasoning, leading to more effective training iterations.
+    </Tip>
+  </Tab>
+  <Tab title="Small Model Usage">
+    If you must use smaller models for training evaluation, be aware of these constraints:
+
+    ```python
+    # Using a smaller model (expect some limitations)
+    llm = LLM(model="huggingface/microsoft/Phi-3-mini-4k-instruct")
+    ```
+
+    <Warning>
+      While CrewAI includes optimizations for small models, expect less reliable and less nuanced evaluation results that may require more human intervention during training.
+    </Warning>
+  </Tab>
+</Tabs>