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README.md

@@ -1,9 +1,14 @@
 ---
+language:
+- en
+license: apache-2.0
 library_name: Transformers
 tags:
+- nlp
 - text-classification
-- transformers
 - argilla
+- transformers
+dataset_name: argilla/emotion
 ---
 
 <!-- This model card has been generated automatically according to the information the `ArgillaTrainer` had access to. You
@@ -15,7 +20,7 @@ This model has been created with [Argilla](https://docs.argilla.io), trained wit
 
 <!-- Provide a quick summary of what the model is/does. -->
 
-
+This is a sample model finetuned from prajjwal1/bert-tiny.
 
 ## Model training
 
@@ -23,22 +28,23 @@ Training the model using the `ArgillaTrainer`:
 
 ```python
 # Load the dataset:
-dataset = FeedbackDataset.from_argilla("...")
+dataset = FeedbackDataset.from_huggingface("argilla/emotion")
 
 # Create the training task:
-task = TrainingTask.for_text_classification(text=dataset.field_by_name("text"), label=dataset.question_by_name("question-3"))
+task = TrainingTask.for_text_classification(text=dataset.field_by_name("text"), label=dataset.question_by_name("label"))
 
 # Create the ArgillaTrainer:
 trainer = ArgillaTrainer(
     dataset=dataset,
     task=task,
     framework="transformers",
-    model="bert-base-cased",
+    model="prajjwal1/bert-tiny",
 )
 
 trainer.update_config({
     "logging_steps": 1,
-    "num_train_epochs": 1
+    "num_train_epochs": 1,
+    "output_dir": "tmp"
 })
 
 trainer.train(output_dir="None")
@@ -56,14 +62,20 @@ trainer.predict("This is awesome!")
 
 <!-- Provide a longer summary of what this model is. -->
 
-
+Model trained with `ArgillaTrainer` for demo purposes
 
 - **Developed by:** [More Information Needed]
 - **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
+- **Model type:** Finetuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) for demo purposes
+- **Language(s) (NLP):** ['en']
+- **License:** apache-2.0
+- **Finetuned from model [optional]:** prajjwal1/bert-tiny
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** N/A
+
 
 <!--
 ## Uses
@@ -134,7 +146,7 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
 ### Framework Versions
 
 - Python: 3.10.7
-- Argilla: 1.17.0-dev
+- Argilla: 1.19.0-dev
 
 <!--
 ## Citation [optional]