--- # For reference on model card metadata, see the spec: https://github.com/netgvarun2012/VirtualTherapist # Doc / guide: https://huggingface.co/docs/hub/model-cards {} --- # Model Card for Model ID This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/netgvarun2012/VirtualTherapist). ## Model Details ### Model Description A MultiModal architecture model that was created and finetuned jointly by concatenating Hubert and BERT embeddings. Hubert model was fine-tuned with a classification head on preprocessed audio and emotion labels in supervised manner. BERT was trained on text transcrition embeddings. Model can accurately recognize emotions classes- Angry,Sad,Fearful,Happy,Disgusted,Surprised,Calm with ~80% accuracy. - **Developed by:** [https://www.linkedin.com/in/sharmavaruncs/] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [MultiModal - Text and Audio based] - **Language(s) (NLP):** [NLP, Speech processing] - **Finetuned from model [optional]:** [https://huggingface.co/docs/transformers/model_doc/hubert] ### Model Sources [optional] - **Repository:** [https://github.com/netgvarun2012/VirtualTherapist/] - **Paper [optional]:** [https://github.com/netgvarun2012/VirtualTherapist/blob/main/documentation/Speech_and_Text_based_MultiModal_Emotion_Recognizer.pdf] - **Demo [optional]:** [https://huggingface.co/spaces/netgvarun2005/VirtualTherapist] ## Uses 'Virtual Therapist' app - an Intelligent speech and text input based assistant that can decipher emotions and generate therapeutic messages based on the Emotional state of the user. Emotions recognized - Angry,Sad,Fearful,Happy,Disgusted,Surprised,Calm with ~80% accuracy. ### Direct Use [More Information Needed] ### Downstream Use [optional] [More Information Needed] ### Out-of-Scope Use [More Information Needed] ## Bias, Risks, and Limitations [More Information Needed] ### Recommendations Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data [More Information Needed] ### Training Procedure #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed] #### Speeds, Sizes, Times [optional] [More Information Needed] ## Evaluation ### Testing Data, Factors & Metrics #### Testing Data [More Information Needed] #### Factors [More Information Needed] #### Metrics [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] [More Information Needed] ## Environmental Impact Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]