Model Card for Model ID
Model Details
precious practice
future works
-単語列はコンパクト
-類義語を列挙
-一文に一意味に整形
-逆伝搬を考え
-勾配消失対策
-バースト性、本当のラベル
-Zipf則
Model Description
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by: [M M]
- Funded by [optional]: []
- Shared by [optional]: []
- Model type: []
- Language(s) (NLP): [Japanese]
- License: [More Information Needed]
- Finetuned from model [optional]: []
Model Sources [optional]
- Repository: []
- Paper [optional]: []
- Demo [optional]: []
Uses
Direct Use
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Downstream Use [optional]
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Out-of-Scope Use
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Bias, Risks, and Limitations
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Recommendations
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.
[llm-jp-3 1]
Training Details
Training Data
[ichikara-instruction-003-001-1.json]
Training Procedure
Preprocessing [optional]
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Training Hyperparameters
Speeds, Sizes, Times [optional]
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Evaluation
Testing Data, Factors & Metrics
Testing Data
[elyza-tasks-100-TV_0.jsonl]
Factors
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Metrics
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Results
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Summary
Model Examination [optional]
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Environmental Impact
Carbon emissions can be estimated using the
Machine Learning Impact calculator presented in
Lacoste et al. (2019).
- Hardware Type: []
- Hours used: [3h]
- Cloud Provider: [ ? ]
- Compute Region: [ Japan ?]
- Carbon Emitted: []
Technical Specifications [optional]
Model Architecture and Objective
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Compute Infrastructure
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Hardware
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Software
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Citation [optional]
BibTeX:
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APA:
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Glossary [optional]
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More Information [optional]
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Model Card Authors [optional]
[M M]
Model Card Contact
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