Update README.md

README.md

@@ -2,14 +2,36 @@
 tags:
 - autotrain
 - text-generation
+- pytorch
 widget:
-- text: "I love AutoTrain because "
-license: other
+- text: 'I love AutoTrain because '
+license: apache-2.0
+datasets:
+- Amod/mental_health_counseling_conversations
+library_name: peft
 ---
 
 # Model Trained Using AutoTrain
 
-This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
+This model was trained using AutoTrain and is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the [mental_health_counseling_conversations](https://huggingface.co/datasets/Amod/mental_health_counseling_conversations) dataset.      
+For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).     
+
+## Model description
+
+A Mistral-7B-Instruct-v0.2 model finetuned on a corpus of mental health conversations between a psychologist and a user.      
+The intention was to create a mental health assistant, "Connor", to address user questions based on responses from a psychologist.
+
+## Training data
+
+The model is finetuned on a corpus of mental health conversations between a psychologist and a client, in the form of context - response pairs. This dataset is a collection of questions and answers sourced from two online counseling and therapy platforms. The questions cover a wide range of mental health topics, and the answers are provided by qualified psychologists.         
+Dataset found here :-      
+* [Kaggle](https://www.kaggle.com/datasets/thedevastator/nlp-mental-health-conversations)
+* [Huggingface](https://huggingface.co/datasets/Amod/mental_health_counseling_conversations)
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+TODO
 
 # Usage
 
@@ -17,7 +39,7 @@ This model was trained using AutoTrain. For more information, please visit [Auto
 import torch
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
-model_path = "GRMenon/Mental-Mistral-7B-Instruct-AutoTrain"
+model_path = "GRMenon/mental-mistral-7b-instruct-autotrain"
 
 tokenizer = AutoTokenizer.from_pretrained(model_path)
 model = AutoModelForCausalLM.from_pretrained(