MathMate
Collection
Capstone Project LLM models
•
5 items
•
Updated
Mathmate-7B-DELLA is a merge of the following models using LazyMergekit:
models:
- model: AI-MO/NuminaMath-7B-TIR
parameters:
density: 0.5
weight: 0.3
- model: deepseek-ai/DeepSeek-Prover-V1.5-RL
parameters:
density: 0.5
weight: 0.2
merge_method: della
base_model: deepseek-ai/deepseek-math-7b-base
parameters:
normalize: true
dtype: bfloat16
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Haleshot/Mathmate-7B-DELLA"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
Evaluation results using LLMAutoeval:
Model | AGIEval | GPT4All | TruthfulQA | Bigbench | Average |
---|---|---|---|---|---|
Mathmate-7B-DELLA | 21.95 | 36.5 | 48.08 | 28.89 | 33.86 |
Task | Version | Metric | Value | Stderr |
---|---|---|---|---|
agieval_aqua_rat | 0 | acc | 21.26 | 2.57 |
acc_norm | 22.05 | 2.61 | ||
agieval_logiqa_en | 0 | acc | 20.89 | 1.59 |
acc_norm | 25.65 | 1.71 | ||
agieval_lsat_ar | 0 | acc | 21.74 | 2.73 |
acc_norm | 19.57 | 2.62 | ||
agieval_lsat_lr | 0 | acc | 13.92 | 1.53 |
acc_norm | 18.82 | 1.73 | ||
agieval_lsat_rc | 0 | acc | 21.19 | 2.50 |
acc_norm | 18.96 | 2.39 | ||
agieval_sat_en | 0 | acc | 24.76 | 3.01 |
acc_norm | 21.36 | 2.86 | ||
agieval_sat_en_without_passage | 0 | acc | 27.18 | 3.11 |
acc_norm | 23.30 | 2.95 | ||
agieval_sat_math | 0 | acc | 25.45 | 2.94 |
acc_norm | 25.91 | 2.96 |
Average: 21.95%
Task | Version | Metric | Value | Stderr |
---|---|---|---|---|
arc_challenge | 0 | acc | 22.61 | 1.22 |
acc_norm | 25.68 | 1.28 | ||
arc_easy | 0 | acc | 25.25 | 0.89 |
acc_norm | 25.08 | 0.89 | ||
boolq | 1 | acc | 52.02 | 0.87 |
hellaswag | 0 | acc | 25.77 | 0.44 |
acc_norm | 26.09 | 0.44 | ||
openbookqa | 0 | acc | 18.40 | 1.73 |
acc_norm | 28.80 | 2.03 | ||
piqa | 0 | acc | 51.31 | 1.17 |
acc_norm | 50.11 | 1.17 | ||
winogrande | 0 | acc | 47.75 | 1.40 |
Average: 36.5%
Task | Version | Metric | Value | Stderr |
---|---|---|---|---|
truthfulqa_mc | 1 | mc1 | 22.77 | 1.47 |
mc2 | 48.08 | 1.70 |
Average: 48.08%
Task | Version | Metric | Value | Stderr |
---|---|---|---|---|
bigbench_causal_judgement | 0 | multiple_choice_grade | 49.47 | 3.64 |
bigbench_date_understanding | 0 | multiple_choice_grade | 13.55 | 1.78 |
bigbench_disambiguation_qa | 0 | multiple_choice_grade | 30.23 | 2.86 |
bigbench_geometric_shapes | 0 | multiple_choice_grade | 10.03 | 1.59 |
exact_str_match | 0.00 | 0.00 | ||
bigbench_logical_deduction_five_objects | 0 | multiple_choice_grade | 19.40 | 1.77 |
bigbench_logical_deduction_seven_objects | 0 | multiple_choice_grade | 14.00 | 1.31 |
bigbench_logical_deduction_three_objects | 0 | multiple_choice_grade | 36.67 | 2.79 |
bigbench_movie_recommendation | 0 | multiple_choice_grade | 23.60 | 1.90 |
bigbench_navigate | 0 | multiple_choice_grade | 47.10 | 1.58 |
bigbench_reasoning_about_colored_objects | 0 | multiple_choice_grade | 13.05 | 0.75 |
bigbench_ruin_names | 0 | multiple_choice_grade | 53.79 | 2.36 |
bigbench_salient_translation_error_detection | 0 | multiple_choice_grade | 15.63 | 1.15 |
bigbench_snarks | 0 | multiple_choice_grade | 46.96 | 3.72 |
bigbench_sports_understanding | 0 | multiple_choice_grade | 49.70 | 1.59 |
bigbench_temporal_sequences | 0 | multiple_choice_grade | 25.80 | 1.38 |
bigbench_tracking_shuffled_objects_five_objects | 0 | multiple_choice_grade | 19.76 | 1.13 |
bigbench_tracking_shuffled_objects_seven_objects | 0 | multiple_choice_grade | 14.69 | 0.85 |
bigbench_tracking_shuffled_objects_three_objects | 0 | multiple_choice_grade | 36.67 | 2.79 |
Average: 28.89%
Average score: 33.86%
Elapsed time: 03:52:09