Update README.md

README.md

@@ -1,67 +1,63 @@
----
-library_name: transformers
-tags:
-- generated_from_trainer
-model-index:
-- name: llama3.2-1B-Function-calling
-  results: []
-datasets:
-- Salesforce/xlam-function-calling-60k
-language:
-- en
-base_model:
-- meta-llama/Llama-3.2-1B
----
+library_name: transformers  
+tags:  
+- generated_from_trainer  
+model-index:  
+- name: llama3.2-1B-Function-calling  
+  results: []  
+datasets:  
+- Salesforce/xlam-function-calling-60k  
+language:  
+- en  
+base_model:  
+- meta-llama/Llama-3.2-1B  
 
-<!-- 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. -->
+---
 
 # llama3.2-1B-Function-calling
 
-This model was trained from scratch on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.1491
+**⚠️ Important: This model is still under development and has not been fully fine-tuned. It is not yet suitable for use in production and should be treated as a work-in-progress. The results and performance metrics shared here are preliminary and subject to change.**
 
 ## Model description
 
-More information needed
+This model was trained from scratch on an unknown dataset and is intended for function-calling tasks. As it is still in early stages, further development is required to optimize its performance.
 
 ## Intended uses & limitations
 
-More information needed
+Currently, this model is not fully trained or optimized for any specific task. It is intended to handle function-calling tasks but should not be used in production until more comprehensive fine-tuning and evaluation are completed.
 
 ## Training and evaluation data
 
-More information needed
+More information is needed regarding the dataset used for training. The model has not yet been fully evaluated, and additional testing is required to confirm its capabilities.
 
 ## Training procedure
 
 ### Training hyperparameters
 
-The following hyperparameters were used during training:
-- learning_rate: 2e-05
-- train_batch_size: 1
-- eval_batch_size: 1
-- 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: 3
+The following hyperparameters were used during training:  
+- learning_rate: 2e-05  
+- train_batch_size: 1  
+- eval_batch_size: 1  
+- 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: 3  
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch  | Step | Validation Loss |
-|:-------------:|:------:|:----:|:---------------:|
-| 0.3083        | 0.9997 | 1687 | 0.3622          |
-| 0.202         | 2.0    | 3375 | 0.2844          |
+| Training Loss | Epoch  | Step | Validation Loss |  
+|:-------------:|:------:|:----:|:---------------:|  
+| 0.3083        | 0.9997 | 1687 | 0.3622          |  
+| 0.202         | 2.0    | 3375 | 0.2844          |  
 | 0.1655        | 2.9997 | 5061 | 0.1491          |
 
+These results are preliminary, and further training will be necessary to refine the model's performance.
 
-### Framework versions
+## Framework versions
 
-- Transformers 4.45.2
-- Pytorch 2.4.1+cu121
-- Datasets 3.0.1
+- Transformers 4.45.2  
+- Pytorch 2.4.1+cu121  
+- Datasets 3.0.1  
 - Tokenizers 0.20.0