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---
pipeline_tag: text-generation
license: apache-2.0
language:
- en
tags:
- SOLAR-10.7B-v1.0
- Open-platypus-Commercial
base_model: upstage/SOLAR-10.7B-v1.0
datasets:
- kyujinpy/Open-platypus-Commercial
model-index:
- name: T3Q-platypus-SOLAR-10.7B-v1.0
results: []
---
Update @ 2024.03.07
## T3Q-platypus-SOLAR-10.7B-v1.0
This model is a fine-tuned version of upstage/SOLAR-10.7B-v1.0
**Model Developers** Chihoon Lee(chlee10), T3Q
## Training hyperparameters
The following hyperparameters were used during training:
```python
# ๋ฐ์ดํ„ฐ์…‹๊ณผ ํ›ˆ๋ จ ํšŸ์ˆ˜์™€ ๊ด€๋ จ๋œ ํ•˜์ดํผ ํŒŒ๋ผ๋ฏธํ„ฐ
batch_size = 16
num_epochs = 1
micro_batch = 1
gradient_accumulation_steps = batch_size // micro_batch
# ํ›ˆ๋ จ ๋ฐฉ๋ฒ•์— ๋Œ€ํ•œ ํ•˜์ดํผ ํŒŒ๋ผ๋ฏธํ„ฐ
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
# LoRA config
lora_r = 16
lora_alpha = 16
lora_dropout = 0.05
lora_target_modules = ["gate_proj", "down_proj", "up_proj"]
# Tokenizer์—์„œ ๋‚˜์˜ค๋Š” input๊ฐ’ ์„ค์ • ์˜ต์…˜
train_on_inputs = False
add_eos_token = False
# NEFTune params
noise_alpha: int = 5
```
## Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu121
- Datasets 2.13.0
- Tokenizers 0.14.1