transformers pytorch gpt_neox text-generation generated_from_trainer base_model:EleutherAI/polyglot-ko-12.8b base_model:finetune:EleutherAI/polyglot-ko-12.8b license:cc-by-nc-sa-4.0 autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: EleutherAI/polyglot-ko-12.8b
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
model-index:
- name: gollm-instruct-all-in-one-v1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# gollm-instruct-all-in-one-v1

This model is a fine-tuned version of [EleutherAI/polyglot-ko-12.8b](https://huggingface.co/EleutherAI/polyglot-ko-12.8b) on a custom mixed dataset

## Model description

- No-context template

```
아래는 작업을 설명하는 질문어와 추가 컨텍스트를 제공하는 맥락이 함께 제공됩니다. 요청을 적절히 완료하는 답변을 작성하세요.

### 질문:
{instruction}

### 답변:

```

- With context template

```
아래는 작업을 설명하는 질문어와 추가 컨텍스트를 제공하는 맥락이 함께 제공됩니다. 요청을 적절히 완료하는 답변을 작성하세요.

### 맥락:
{input}

### 질문:
{instruction}

### 답변:

```

## Intended uses & limitations

More information needed

## Training and evaluation data

- self-introduction (20 samples)
- Combined KoAlpaca and KULLM - no-context samples only (145.8k samples)
  + KoAlpaca v1.0
  + KoAlpaca v1.1
  + KULLM (Dolly and Vicuna only)
- Naver news summarization (22.2k samples)
- KLUE MRC (17.5k samples)
- KLUE STS (5.6k samples)

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
- saved_checkpoint_at_epoch: 4 (condition: loss < 0.3)

### Training results

| Training Loss | Epoch |  Step  |
|:-------------:|:-----:|:------:|
| 1.5688        | 1.0   |  11947 |
| 1.0424        | 2.0   |  23895 |
| 0.5542        | 3.0   |  35843 |
| 0.2548        | 4.0   |  47791 |
| 0.1479        | 5.0   |  59738 |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3
