Model Card for kobart-base-v2
Model Details
Model Description
BART(Bidirectional and Auto-Regressive Transformers)λ μ
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- Developed by: More information needed
- Shared by [Optional]: Heewon(Haven) Jeon
- Model type: Feature Extraction
- Language(s) (NLP): Korean
- License: MIT
- Parent Model: BART
- Resources for more information:
Uses
Direct Use
This model can be used for the task of Feature Extraction.
Downstream Use [Optional]
More information needed.
Out-of-Scope Use
The model should not be used to intentionally create hostile or alienating environments for people.
Bias, Risks, and Limitations
Significant research has explored bias and fairness issues with language models (see, e.g., Sheng et al. (2021) and Bender et al. (2021)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups.
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.
Training Details
Training Data
Data | # of Sentences |
---|---|
Korean Wiki | 5M |
Other corpus | 0.27B |
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vocab
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Training Procedure
Tokenizer
tokenizers
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Speeds, Sizes, Times
Model | # of params | Type | # of layers | # of heads | ffn_dim | hidden_dims |
---|---|---|---|---|---|---|
KoBART-base |
124M | Encoder | 6 | 16 | 3072 | 768 |
Decoder | 6 | 16 | 3072 | 768 |
Evaluation
Testing Data, Factors & Metrics
Testing Data
More information needed
Factors
More information needed
Metrics
More information needed
Results
NSMC
- acc. : 0.901
The model authors also note in the GitHub Repo:
NSMC(acc) | KorSTS(spearman) | Question Pair(acc) | |
---|---|---|---|
KoBART-base | 90.24 | 81.66 | 94.34 |
Model Examination
More information needed
Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- 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
Technical Specifications [optional]
Model Architecture and Objective
More information needed
Compute Infrastructure
More information needed
Hardware
More information needed
Software
More information needed.
Citation
BibTeX:
More information needed.
Glossary [optional]
More information needed
More Information [optional]
More information needed
Model Card Authors [optional]
Heewon(Haven) Jeon in collaboration with Ezi Ozoani and the Hugging Face team
Model Card Contact
The model authors note in the GitHub Repo:
KoBART
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How to Get Started with the Model
Use the code below to get started with the model.
Click to expand
from transformers import PreTrainedTokenizerFast, BartModel
tokenizer = PreTrainedTokenizerFast.from_pretrained('gogamza/kobart-base-v2')
model = BartModel.from_pretrained('gogamza/kobart-base-v2')
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