---
pipeline_tag: text-generation
license: apache-2.0
language:
- en
tags:
- Open-platypus-Commercial
base_model: liminerity/M7-7b
datasets:
- kyujinpy/Open-platypus-Commercial
model-index:
- name: T3Q-Platypus-Mistral7B
  results: []
---
Update @ 2024.03.07

## T3Q-Platypus-MistralM7-7B

This model is a fine-tuned version of liminerity/M7-7b

**Model Developers** Chihoon Lee(chlee10), T3Q

## Training hyperparameters

The following hyperparameters were used during training:

```python
  # 데이터셋과 훈련 횟수와 관련된 하이퍼 파라미터
  batch_size = 16
  num_epochs = 1
  micro_batch = 1
  gradient_accumulation_steps = batch_size // micro_batch
  
  # 훈련 방법에 대한 하이퍼 파라미터
  cutoff_len = 4096
  lr_scheduler = 'cosine'
  warmup_ratio = 0.06 # warmup_steps = 100
  learning_rate = 4e-4
  optimizer = 'adamw_torch'
  weight_decay = 0.01
  max_grad_norm = 1.0
  
  # Q-LoRA config
  lora_r = 16
  lora_alpha = 16
  lora_dropout = 0.05
  lora_target_modules = ["gate_proj", "down_proj", "up_proj"]
  
  # Tokenizer에서 나오는 input값 설정 옵션
  train_on_inputs = False
  add_eos_token = False
  
  # NEFTune params
  noise_alpha: int = 5
```