---
language:
- en
license: mit
datasets:
- vibhorag101/phr_mental_therapy_dataset
- jerryjalapeno/nart-100k-synthetic
pipeline_tag: text-generation
model-index:
- name: llama-2-7b-chat-hf-phr_mental_health-2048
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc_norm
      value: 52.39
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vibhorag101/llama-2-7b-chat-hf-phr_mental_health-2048
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc_norm
      value: 75.39
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vibhorag101/llama-2-7b-chat-hf-phr_mental_health-2048
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 39.77
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vibhorag101/llama-2-7b-chat-hf-phr_mental_health-2048
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: mc2
      value: 42.89
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vibhorag101/llama-2-7b-chat-hf-phr_mental_health-2048
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 71.19
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vibhorag101/llama-2-7b-chat-hf-phr_mental_health-2048
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 5.91
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vibhorag101/llama-2-7b-chat-hf-phr_mental_health-2048
      name: Open LLM Leaderboard
---
# Model Card

<!-- Provide a quick summary of what the model is/does. -->
- This model is a finetune of the **llama-2-7b-chat-hf** model on a therapy dataset.
- The model aims to provide basic therapy to the users and improve their mental health until they seek professional help.
- The model has been adjusted to encourage giving cheerful responses to the user. The system prompt has been mentioned below.

## Model Details
### Training Hardware
- RTX A5000 24GB
- 48 Core Intel Xeon
- 128GB RAM.
### Model Hyperparameters
- This [training script](https://github.com/phr-winter23/phr-mental-chat/blob/main/finetuneModel/finetuneScriptLLaMA-2.ipynb) was used to do the finetuning.
- The shareGPT format dataset was converted to llama-2 training format using this [script](https://github.com/phr-winter23/phr-mental-chat/blob/main/finetuneModel/llamaDataMaker.ipynb).
- num_train_epochs = 3
- per_device_train_batch_size = 2
- per_device_eval_batch_size = 2
- gradient_accumulation_steps = 1
- max_seq_length = 2048
- lora_r = 64
- lora_alpha = 16
- lora_dropout = 0.1
- use_4bit = True
- bnb_4bit_compute_dtype = "float16"
- bnb_4bit_quant_type = "nf4"
- use_nested_quant = False
- fp16 = False
- bf16 = True
- Data Sample: 1000 (80:20 split)

### Model System Prompt
You are a helpful and joyous mental therapy assistant. Always answer as helpfully and cheerfully as possible, while being safe.  Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content.Please ensure that your responses are socially unbiased and positive in nature.

If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information.

#### Model Training Data

![image/png](https://cdn-uploads.huggingface.co/production/uploads/64eb1e4a55e4f0ecb9c4f406/PsbTFlswJexLuwrJYtvly.png)


# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_vibhorag101__llama-2-7b-chat-hf-phr_mental_health-2048)

| Metric                | Value                     |
|-----------------------|---------------------------|
| Avg.                  | 42.84   |
| ARC (25-shot)         | 52.39          |
| HellaSwag (10-shot)   | 75.39    |
| MMLU (5-shot)         | 39.77         |
| TruthfulQA (0-shot)   | 42.89   |
| Winogrande (5-shot)   | 71.19   |
| GSM8K (5-shot)        | 5.91        |
| DROP (3-shot)         | 12.3         |

# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_vibhorag101__llama-2-7b-chat-hf-phr_mental_health-2048)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |47.92|
|AI2 Reasoning Challenge (25-Shot)|52.39|
|HellaSwag (10-Shot)              |75.39|
|MMLU (5-Shot)                    |39.77|
|TruthfulQA (0-shot)              |42.89|
|Winogrande (5-shot)              |71.19|
|GSM8k (5-shot)                   | 5.91|