A fine-tuned version of
unsloth/Qwen3.5-2B
trained on
EventPlanning ShareGPT
data using
Auto-SFT
— an automated hyperparameter search and supervised fine-tuning pipeline.
The base model was adapted to follow the style and content of the
EventPlanning ShareGPT
dataset. Expect improved performance on tasks similar to those represented in the training data.
Model Details
Property
Value
Base model
unsloth/Qwen3.5-2B
Training data
data/EventPlanning-ShareGPT.json
Fine-tuning epochs
2
Fine-tuning date
2026-10-08
Fine-tuning method
LoRA (merged to full 16-bit)
Training Hyperparameters
LoRA
Parameter
Value
r
64
alpha
64
dropout
0.03
target_modules
['q_proj', 'v_proj', 'k_proj', 'o_proj']
Training
Parameter
Value
learning_rate
0.0002
batch_size
1
gradient_accumulation_steps
2
warmup_ratio
0.05
max_seq_length
2048
quantization
none
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("theprint/EventPlanner-v1-2B")
tokenizer = AutoTokenizer.from_pretrained("theprint/EventPlanner-v1-2B")
Generated by
Auto-SFT
— automated LoRA fine-tuning with hyperparameter search.
Runs of theprint EventPlanner-v1-2B on huggingface.co
15
Total runs
0
24-hour runs
3
3-day runs
15
7-day runs
15
30-day runs
More Information About EventPlanner-v1-2B huggingface.co Model
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