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---
language:
- en
license: mit
datasets:
- vibhorag101/phr_mental_therapy_dataset
- jerryjalapeno/nart-100k-synthetic
pipeline_tag: text-generation
model-index:
- name: llama-2-13b-chat-hf-phr_mental_therapy
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: 38.82
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vibhorag101/llama-2-13b-chat-hf-phr_mental_therapy
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: 72.76
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vibhorag101/llama-2-13b-chat-hf-phr_mental_therapy
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: 23.12
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vibhorag101/llama-2-13b-chat-hf-phr_mental_therapy
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: 46.92
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vibhorag101/llama-2-13b-chat-hf-phr_mental_therapy
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: 65.59
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vibhorag101/llama-2-13b-chat-hf-phr_mental_therapy
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: 7.81
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vibhorag101/llama-2-13b-chat-hf-phr_mental_therapy
name: Open LLM Leaderboard
---
# Model Card
<!-- Provide a quick summary of what the model is/does. -->
- This model is a finetune of the **llama-2-13b-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 = 2
- per_device_train_batch_size = 2
- per_device_eval_batch_size = 2
- gradient_accumulation_steps = 1
- max_seq_length = 4096
- 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
### Model Benchmarks
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_vibhorag101__llama-2-13b-chat-hf-phr_mental_therapy)
| Metric | Value |
|-----------------------|---------------------------|
| Avg. | 42.5 |
| ARC (25-shot) | 38.82 |
| HellaSwag (10-shot) | 72.76 |
| MMLU (5-shot) | 23.12 |
| TruthfulQA (0-shot) | 46.92 |
| Winogrande (5-shot) | 65.59 |
| GSM8K (5-shot) | 7.81 |
# [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-2-13b-chat-hf-phr_mental_therapy)
| Metric |Value|
|---------------------------------|----:|
|Avg. |42.50|
|AI2 Reasoning Challenge (25-Shot)|38.82|
|HellaSwag (10-Shot) |72.76|
|MMLU (5-Shot) |23.12|
|TruthfulQA (0-shot) |46.92|
|Winogrande (5-shot) |65.59|
|GSM8k (5-shot) | 7.81|
|