Improve comments

utils/components_creator.py

@@ -126,7 +126,7 @@ def add_training_args_1_bis() -> Set[Component]:
     logging_steps = gr.Slider(1, 100, step=1, value=10, label="logging_steps",
                               info="Number of update steps between two logs if logging_strategy='steps'",
                               interactive=True, elem_id=LOGGING_STEPS_ID)
-    per_device_train_batch_size = gr.Slider(1, 64, step=1, value=4, label="per_device_train_batch_size",
+    per_device_train_batch_size = gr.Slider(1, 64, step=1, value=3, label="per_device_train_batch_size",
                                             info="Batch size per device during training.",
                                             interactive=True, elem_id=PER_DEVICE_TRAIN_BATCH_SIZE)
     save_strategy = gr.Radio(['no', 'epoch', 'steps'], label="save_strategy",

utils/notebook_generator.py

@@ -61,10 +61,18 @@ def create_login_hf_cells(cells: list, should_login: bool = False, model_name: O
     text_cell = nbf.v4.new_markdown_cell(
         "## Login to HF")
 
-    text_1 = "Login with our `HF_TOKEN` in order to push the finetuned model to `huggingface_hub`."
+    text_1 = """
+    Login with `HF_TOKEN` in order to push the fine-tuned model to `huggingface_hub`.
+    
+    Replace `HF_TOKEN` with a valid Token.
+    """
 
     if should_login:
-        text_1 = f"Login with our `HF_TOKEN` in order to load **{model_name}** from `huggingface_hub`."
+        text_1 = f"""    
+    Login with `HF_TOKEN` in order to load **{model_name}** from `huggingface_hub`.
+
+     Replace `HF_TOKEN` with a valid Token.
+    """
 
     text_cell1 = nbf.v4.new_markdown_cell(text_1)
     code = """
@@ -87,7 +95,7 @@ login(
 def create_datasets_cells(cells: list, dataset: FTDataSet, seed: int):
     text_cell = nbf.v4.new_markdown_cell("# Load and Prepare the Dataset")
     text = 'The dataset is already formatted in a conversational format, which is supported by [trl](' \
-           'https://huggingface.co/docs/trl/index/). '
+           'https://huggingface.co/docs/trl/index/), and ready for supervised finetuning.'
     text_format = """
 **Conversational format:**
 
@@ -236,7 +244,7 @@ peft_config = LoraConfig(
     text = """The `SFTTrainer` provides native integration with `peft`, simplifying the process of efficiently tuning 
     Language Models (LLMs) using techniques such as [LoRA](
     https://magazine.sebastianraschka.com/p/practical-tips-for-finetuning-llms). The only requirement is to create 
-    our `LoraConfig` and pass it to the `SFTTrainer`. 
+    the `LoraConfig` and pass it to the `SFTTrainer`. 
     """
 
     code_cell = nbf.v4.new_code_cell(code)
@@ -433,7 +441,7 @@ for item in os.listdir(source_folder):
 
 
 def push_to_hub_cells(cells: list, output_dir):
-    text = f"## Pushing '{output_dir}' to our Hugging Face account."
+    text = f"## Pushing '{output_dir}' to the Hugging Face account."
     code = f"""
 from huggingface_hub import HfApi, HfFolder, Repository