aeolian83
/

llama_ko_sft_gugugo_experi_01

@@ -18,6 +18,8 @@ transformers와 trl을 이용하여 QLoRA로 훈련 진행
 Dataset은 https://huggingface.co/datasets/squarelike/OpenOrca-gugugo-ko
 ## Model Details
@@ -27,76 +29,39 @@ Dataset은 https://huggingface.co/datasets/squarelike/OpenOrca-gugugo-ko
 ## Uses
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 ```
-### Direct Use
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-## How to Get Started with the Model
-Use the code below to get started with the model.
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 ## Training Details
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-### Training Procedure
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-#### Preprocessing [optional]
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 #### Training Hyperparameters
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 ## Evaluation
@@ -104,94 +69,35 @@ Use the code below to get started with the model.
 ### Testing Data, Factors & Metrics
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 Dataset은 https://huggingface.co/datasets/squarelike/OpenOrca-gugugo-ko
+QLoRA 훈련 테스트를 위한 훈련 결과물
 ## Model Details
 ## Uses
 <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+### Prompt template
 ```
+"""
+### instruction:
 ### intput:
 ### output:
+"""
 ```
 ## Training Details
 #### Training Hyperparameters
+- **Training regime:** [bf16 mixed precision] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+- <PAD>토큰 추가 후 right 패딩사이드 지정하여 진행
+- LoRA config
+    ```
+peft_config = LoraConfig(
+    lora_alpha=16,
+    lora_dropout=0.1,
+    r=64,
+    bias="none",
+    task_type="CAUSAL_LM"
+)
+    ```
 ## Evaluation
 ### Testing Data, Factors & Metrics
+link: https://github.com/Beomi/ko-lm-evaluation-harness
+results/all/aeolian83/llama_ko_sft_gugugo_experi_01
+|                                  |        0 |        5 |
+|:---------------------------------|---------:|---------:|
+| kobest_boolq (macro_f1)          | 0.588382 | 0.384051 |
+| kobest_copa (macro_f1)           | 0.749558 | 0.778787 |
+| kobest_hellaswag (macro_f1)      | 0.439247 | 0.439444 |
+| kobest_sentineg (macro_f1)       | 0.448283 | 0.934415 |
+| kohatespeech (macro_f1)          | 0.244828 | 0.371245 |
+| kohatespeech_apeach (macro_f1)   | 0.337434 | 0.394607 |
+| kohatespeech_gen_bias (macro_f1) | 0.135272 | 0.461714 |
+| korunsmile (f1)                  | 0.254562 | 0.315907 |
+| nsmc (acc)                       | 0.61248  | 0.84256  |
+| pawsx_ko (acc)                   | 0.5615   | 0.5365   |
+results/all/beomi/llama-2-ko-7b
+|                                  |        0 |        5 |       10 |       50 |
+|:---------------------------------|---------:|---------:|---------:|---------:|
+| kobest_boolq (macro_f1)          | 0.612147 | 0.682832 | 0.713392 | 0.71622  |
+| kobest_copa (macro_f1)           | 0.759784 | 0.799843 | 0.807907 | 0.829976 |
+| kobest_hellaswag (macro_f1)      | 0.447951 | 0.460632 | 0.464623 | 0.458628 |
+| kobest_sentineg (macro_f1)       | 0.3517   | 0.969773 | 0.977329 | 0.97481  |
+| kohatespeech (macro_f1)          | 0.314636 | 0.383336 | 0.357491 | 0.366585 |
+| kohatespeech_apeach (macro_f1)   | 0.346127 | 0.567627 | 0.583391 | 0.629269 |
+| kohatespeech_gen_bias (macro_f1) | 0.204651 | 0.509189 | 0.471078 | 0.451119 |
+| korunsmile (f1)                  | 0.290663 | 0.306208 | 0.304279 | 0.343946 |
+| nsmc (acc)                       | 0.57942  | 0.84242  | 0.87368  | 0.8939   |
+| pawsx_ko (acc)                   | 0.538    | 0.52     | 0.5275   | 0.5195   |