Update README.md

README.md

@@ -4,74 +4,11 @@ base_model: meta-llama/Llama-2-7b-chat-hf
 ---
 
 # Model Card for Model ID
-
+## euneeei/hw-llama-2-7B-nsmc
 <!-- Provide a quick summary of what the model is/does. -->
 
 
 
-## Model Details
-
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
-
-
-
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## 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. -->
-
-### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
-
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-
-## How to Get Started with the Model
-
-Use the code below to get started with the model.
-
-[More Information Needed]
 
 ## Training Details
 
@@ -79,124 +16,139 @@ Use the code below to get started with the model.
 
 <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
 
-[More Information Needed]
-
-### Training Procedure 
-
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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-#### Preprocessing [optional]
-
-[More Information Needed]
-
-
-#### Training Hyperparameters
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-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
-
-## Evaluation
-
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
+- train dataset : 3000개
+- test dataset: 1000개
 
-#### Metrics
+## **1. midm으로 정확도 0.91 나왔던 @dataclass파라미터그대로**
+- ### learning_rate : 2e-4
 
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+|     | precision | recall | f1-score | support|
+|----|----|----|-------|------|
+negative| 0.81 | 0.91 | 0.85 | 492
+positive | 0.90 | 0.79 | 0.84 | 508
+accuracy | | | 0.85 | 1000
+macro avg | 0.85 | 0.85 | 0.85 | 1000
+weighted avg | 0.85 | 0.85 | 0.85 | 1000
 
-[More Information Needed]
 
-### Results
+- ### confusion Matrix:
+  ### [[ 446, 46 ]
+  ### [106, 402]]
 
-[More Information Needed]
+- ### accuracy 0.85으로 0.90에 못 미추어, learning rate를 더 조절하기로 했습니다. 또한 실제로는 '긍정'인데 '부정'으로 판단한 경우가 높게 나왔습니다.
 
-#### Summary
+## **2. learning_rate 2e-4 -> 1e-4로 변경**
 
+- ### learning_rate : 1e-4
 
 
-## Model Examination [optional]
+|     | precision | recall | f1-score | support|
+|----|----|----|-------|------|
+negative| 0.82 | 0.88 | 0.85 | 492
+positive | 0.87 | 0.81 | 0.84 | 508
+accuracy | | | 0.84 | 1000
+macro avg | 0.84 | 0.84 | 0.84 | 1000
+weighted avg | 0.84 | 0.84 | 0.84 | 1000
 
-<!-- Relevant interpretability work for the model goes here -->
 
-[More Information Needed]
+- ### confusion Matrix:
+  ### [[ 431, 61 ]
+  ### [96, 412]]
 
-## Environmental Impact
+- ### 학습률 변경전보다 전반적으로 좋아지지 않았습니다. 따라서 학습률을 높여보기로 결정했습니다.
 
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+## **3. learning_rate 1e-4 -> 4e-4로 변경**
 
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+- ### learning_rate 1e-4와 크게 달라진 점이 없었습니다. 그래서 다른 것을 조정을 하기로 했습니다.
 
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
+## **4. 배치 사이즈를 증가.**
 
-## Technical Specifications [optional]
+- ### 메모리 이슈로 script_args의 seq_length = 450으로 줄였습니다.  
 
-### Model Architecture and Objective
+- ### 그러나 계속 메모리 부족으로 학습 불가
+            per_device_train_batch_size=1
+            ->per_device_train_batch_size=2
+            per_device_eval_batch_size=1,
+            ->per_device_eval_batch_size=2
 
-[More Information Needed]
 
-### Compute Infrastructure
+## **5. gradient_accumulation_steps 증가**
 
-[More Information Needed]
+- ### 배치 사이즈 증가 대신 gradient accumulation step 변경하기로 함.
+- ### 메모리 부족 예방으로 script_args의 seq_length = 450으로 줄임  
+            gradient_accumulation_steps=2,
+            -> gradient_accumulation_steps=4
+            -> gradient_accumulation_steps=8
+            
+            
 
-#### Hardware
+|     | precision | recall | f1-score | support|
+|----|----|----|-------|------|
+negative| 0.85 | 0.88 | 0.87 | 492
+positive | 0.88 | 0.85 | 0.87 | 508
+accuracy | | | 0.87 | 1000
+macro avg | 0.87 | 0.87 | 0.87 | 1000
+weighted avg | 0.87 | 0.87 | 0.87 | 1000
 
-[More Information Needed]
 
-#### Software
+- ### confusion Matrix:
+  ### [[ 435, 57 ]
+  ### [77, 431]]
 
-[More Information Needed]
+  - ### 정확도 0.90을 넘기지는 못했지만, "부정"을 맞추는 비율이 많아졌습니다.
 
-## Citation [optional]
+## **6. weight_decay 감소, learning_rate 증가**
 
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+            weight_decay=0.03
+            -> weight_decay=0.01
+            learning_rate=4e-4
+            -> learning_rate=5e-4
 
-**BibTeX:**
 
-[More Information Needed]
 
-**APA:**
+|     | precision | recall | f1-score | support|
+|----|----|----|-------|------|
+negative| 0.85 | 0.89 | 0.87 | 492
+positive | 0.89 | 0.85 | 0.87 | 508
+accuracy | | | 0.87 | 1000
+macro avg | 0.87 | 0.87 | 0.87 | 1000
+weighted avg | 0.87 | 0.87 | 0.87 | 1000
 
-[More Information Needed]
 
-## Glossary [optional]
+- ### 결과 : 0.87, 5번과 거의 차이가 없습니다.
 
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+## **7. max_step 제한 없애기**
 
-[More Information Needed]
+|     | precision | recall | f1-score | support|
+|----|----|----|-------|------|
+negative| 0.86 | 0.89 | 0.87 | 492
+positive | 0.89 | 0.86 | 0.87 | 508
+accuracy | | | 0.87 | 1000
+macro avg | 0.87 | 0.87 | 0.87 | 1000
+weighted avg | 0.87 | 0.87 | 0.87 | 1000
 
-## More Information [optional]
 
-[More Information Needed]
+- ### confusion Matrix:
+  ### [[ 436, 56 ]
+  ### [70, 438]]
 
-## Model Card Authors [optional]
+-### 아주 조금씩 더 정확해지고 있으나, 정확도 0.87에서 큰 변화가 없습니다.
 
-[More Information Needed]
+## **8. learning rate 더 줄이기
+|     | precision | recall | f1-score | support|
+|----|----|----|-------|------|
+negative| 0.84 | 0.90 | 0.87 | 492
+positive | 0.89 | 0.84 | 0.86 | 508
+accuracy | | | 0.87 | 1000
+macro avg | 0.87 | 0.87 | 0.87 | 1000
+weighted avg | 0.87 | 0.87 | 0.87 | 1000
 
-## Model Card Contact
+- ### confusion Matrix:
+  ### [[ 441, 51 ]
+  ### [83, 425]]
 
-[More Information Needed]
+- ### 이전보다 '긍정'을 더 잘 맞추지만, '부정'을 맞추는 경우가 줄어들었습니다.
+결과적으로 정확도 0.87으로 학습을 마치겠습니다.
 
 
 ### Framework versions