File size: 1,115 Bytes
afeba10 f7a230f 4b1bc0e f7a230f 7dff9e7 f7a230f 4b1bc0e afeba10 f7a230f c53f71b f7a230f 7dff9e7 f7a230f 4b1bc0e f7a230f 726a252 f7a230f 4b1bc0e f7a230f a1edf0e f7a230f a1edf0e f7a230f 4b1bc0e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 |
---
license: apache-2.0
tags:
- generated_from_trainer
- polyglot-ko
- gpt-neox
- KoAlpaca
model-index:
- name: KoAlpaca-Polyglot-12.8B
results: []
language:
- ko
datasets:
- KoAlpaca-v1.1b
pipeline_tag: text-generation
---
Update @ 2023.06.01
- Add Safetensor sharded model weight (max shard = 1GB)
# KoAlpaca-Polyglot-12.8B (v1.1b)
This model is a fine-tuned version of [EleutherAI/polyglot-ko-12.8b](https://huggingface.co/EleutherAI/polyglot-ko-12.8b) on a KoAlpaca Dataset v1.1b
Detail Codes are available at [KoAlpaca Github Repository](https://github.com/Beomi/KoAlpaca)
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 1
- seed: 42
- distributed_type: multi-GPU (A100 80G)
- num_devices: 4
- gradient_accumulation_steps: 64
- total_train_batch_size: 256
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2.0
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3 |