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README.md

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 ---
-license: cc-by-sa-4.0
+license: cc-by-nc-4.0
+base_model: 42dot/42dot_LLM-PLM-1.3B
+tags:
+- generated_from_trainer
+model-index:
+- name: AIFT-42dot_LLM-PLM-1.3B-ao-instruct-all-v0.4-merge-ff-e1
+  results: []
 ---
-<h1>instruct 모델 v0.4</h1>
-
-<b><학습 데이터 구축></b>
-
-Open-Orca-ko 데이터를 분석하여 태스크를 추출한 뒤
-해당 태스크에 맞춰서 NLP 관련 오픈소스 데이터를 활용하여 학습데이터를 자체적으로 
-약 4만건(역사, 과학, 수학, 기계독해, 리뷰 분석) 구축하였고, 
-그 외에 Open-Orca-Ko에서 데이터를 일부 필터링하여 정제해거나 KoBEST 데이터를 함께 추가하였습니다.
-aihub 일반상식 및 기계독해 데이터를 활용하여 추가로 학습 데이터를 구축(형태소 관련, 기계독해 관련 및 요약)
-각종 블로그에서 역사 및 상식 퀴즈를 사람이 직접 학습데이터 형태로 변경
-AI2AI Challenge 데이터를 파파고를 통해 번역 및 오역된 부분을 사람이 직접 수정 하는 작업을 수행
-영어 번역 데이터 영한/한영 데이터 학습 데이터로 활용 진행
-
-총 11만개의 학습데이터로 sft를 진행하였습니다.
-<br>
-현재, 새로운 버전의 모델 학습 및 성능을 위해 Open-Orca 데이터셋 일부를 번역하여 정제 중에 있습니다.
-<br>
-+ 고등학교 역사 문제 및 TruthfulQA 관련 문제 추가를 진행하였습니다.
-+ 각종 it 지식 데이터 추가진행.
-+ 기계독해 관련 학습 데이터를 ChatGPT를 통해서 답변을 얻어 학습
-+ 문법관련 학습 데이터 
-<br>
-###학습 데이터 파일은 비공개입니다. 
-<br>
-<b><학습></b>
-학습은 LoRA를 사용하여 A100 40G *2에서 학습을 진행하였습니다.
-
-<br>
-<b><베이스모델></b>
-42dot-PLM-1.3B 사용하였습니다.
+
+<!-- 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. -->
+
+# AIFT-42dot_LLM-PLM-1.3B-ao-instruct-all-v0.4-merge-ff-e1
+
+This model is a fine-tuned version of [42dot/42dot_LLM-PLM-1.3B](https://huggingface.co/42dot/42dot_LLM-PLM-1.3B) on an unknown dataset.
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 24
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 96
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 1.0
+- mixed_precision_training: Native AMP
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.1.2+cu121
+- Datasets 2.0.0
+- Tokenizers 0.15.0

added_tokens.json

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+  "<||unk||>": 50259
+}

all_results.json

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+{
+    "epoch": 1.0,
+    "train_loss": 0.9609996382012425,
+    "train_runtime": 5748.5662,
+    "train_samples": 39880,
+    "train_samples_per_second": 6.937,
+    "train_steps_per_second": 0.072
+}

config.json

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+{
+  "_name_or_path": "42dot/42dot_LLM-PLM-1.3B",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 50257,
+  "eos_token_id": 50256,
+  "hidden_act": "silu",
+  "hidden_size": 2048,
+  "initializer_range": 0.01,
+  "intermediate_size": 5632,
+  "max_position_embeddings": 4096,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 24,
+  "num_key_value_heads": 32,
+  "pad_token_id": 50258,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "tie_word_embeddings": false,
+  "tokenizer_class": "GPT2TokenizerFast",
+  "torch_dtype": "float32",
+  "transformers_version": "4.36.2",
+  "use_cache": true,
+  "vocab_size": 50304
+}

generation_config.json

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+  "bos_token_id": 50257,
+  "eos_token_id": 50256,
+  "pad_token_id": 50258,
+  "transformers_version": "4.36.2"
+}

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