Model Card for Model ID
Model Details
Model Description
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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Developed by: [an.dong90]
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Model type: [Fine tuned distilled Deepseek R1 Qwen 7B model]
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Language(s) (NLP): [English]
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License: [MIT]
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**Finetuned from model [deepseek-ai/DeepSeek-R1-Distill-Qwen-7B]
Model Sources [optional]
Uses
prompt_test = """Given a student's Conversation History and Current Message, extract the relevant metadata, including emotion type, emotion intensity (1-5), problem type, and counseling strategy.
Then answer the student's Current Message as a counselor based on the metadata. Keep it concise but affirmative.
The counselor must return a Structured JSON Response with these fields: "emotion_type","emotion_intensity", "problem_type", "counseling_strategy","answer".
Student:
Conversation History:
{user_history}
Current Message:
{user_text}
Counselor Structured JSON Response:
"""
FastLanguageModel.for_inference(model)
inputs = tokenizer([prompt_test.format(user_history=user_history,user_text=user_text)], return_tensors="pt").to("cuda")
outputs = model.generate(
input_ids=inputs.input_ids,
attention_mask=inputs.attention_mask,
max_new_tokens=250,
eos_token_id=tokenizer.eos_token_id,
num_return_sequences=1,
temperature=0.6, # deepseek doc recommended 0.6 to balance creativity and coherence, avoiding repetitive or nonsensical outputs.
top_p=0.9, # Reduces repeated phrases
use_cache=True,
)
response = tokenizer.decode(outputs[0],skip_special_tokens=True)
[More Information Needed]
Training Details
Training Data
Training Procedure
Preprocessing [optional]
[More Information Needed]
Training Hyperparameters
- Training regime: [More Information Needed]
Speeds, Sizes, Times [optional]
[More Information Needed]
Evaluation
3 LLMs as judges
DeepSeek R1 Distilled Llama 8B
DeepSeek R1 Distilled Qwen 7B
Mistral 7B v0.3
Assessed generated responses based on empathy, appropriateness, and relevance on scale of 1-5
Metrics proposed on Medium article in similar mental health setting*
Averaged score across judges
Median
Empathy-4.00
Appropriateness-5.00
Relevance-4.33
Testing Data, Factors & Metrics
Testing Data
[More Information Needed]
Factors
[More Information Needed]
Metrics
[More Information Needed]
Results
[More Information Needed]
Summary
