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--- |
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language: ko |
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license: mit |
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tags: |
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- bart |
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--- |
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# Model Card for kobart-base-v2 |
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# Model Details |
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## Model Description |
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[**BART**](https://arxiv.org/pdf/1910.13461.pdf)(**B**idirectional and **A**uto-**R**egressive **T**ransformers)λ μ
λ ₯ ν
μ€νΈ μΌλΆμ λ
Έμ΄μ¦λ₯Ό μΆκ°νμ¬ μ΄λ₯Ό λ€μ μλ¬ΈμΌλ‘ 볡ꡬνλ `autoencoder`μ ννλ‘ νμ΅μ΄ λ©λλ€. νκ΅μ΄ BART(μ΄ν **KoBART**) λ λ
Όλ¬Έμμ μ¬μ©λ `Text Infilling` λ
Έμ΄μ¦ ν¨μλ₯Ό μ¬μ©νμ¬ **40GB** μ΄μμ νκ΅μ΄ ν
μ€νΈμ λν΄μ νμ΅ν νκ΅μ΄ `encoder-decoder` μΈμ΄ λͺ¨λΈμ
λλ€. μ΄λ₯Ό ν΅ν΄ λμΆλ `KoBART-base`λ₯Ό λ°°ν¬ν©λλ€. |
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- **Developed by:** More information needed |
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- **Shared by [Optional]:** Heewon(Haven) Jeon |
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- **Model type:** Feature Extraction |
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- **Language(s) (NLP):** Korean |
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- **License:** MIT |
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- **Parent Model:** BART |
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- **Resources for more information:** |
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- [GitHub Repo](https://github.com/haven-jeon/KoBART) |
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- [Model Demo Space](https://huggingface.co/spaces/gogamza/kobart-summarization) |
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# Uses |
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## Direct Use |
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This model can be used for the task of Feature Extraction. |
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## Downstream Use [Optional] |
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More information needed. |
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## Out-of-Scope Use |
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The model should not be used to intentionally create hostile or alienating environments for people. |
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# Bias, Risks, and Limitations |
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Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups. |
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## Recommendations |
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. |
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# Training Details |
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## Training Data |
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| Data | # of Sentences | |
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|-------|---------------:| |
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| Korean Wiki | 5M | |
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| Other corpus | 0.27B | |
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νκ΅μ΄ μν€ λ°±κ³Ό μ΄μΈ, λ΄μ€, μ±
, [λͺ¨λμ λ§λμΉ v1.0(λν, λ΄μ€, ...)](https://corpus.korean.go.kr/), [μ²μλ κ΅λ―Όμ²μ](https://github.com/akngs/petitions) λ±μ λ€μν λ°μ΄ν°κ° λͺ¨λΈ νμ΅μ μ¬μ©λμμ΅λλ€. |
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`vocab` μ¬μ΄μ¦λ 30,000 μ΄λ©° λνμ μμ£Ό μ°μ΄λ μλμ κ°μ μ΄λͺ¨ν°μ½, μ΄λͺ¨μ§ λ±μ μΆκ°νμ¬ ν΄λΉ ν ν°μ μΈμ λ₯λ ₯μ μ¬λ Έμ΅λλ€. |
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> π, π, π, π
, π€£, .. , `:-)`, `:)`, `-)`, `(-:`... |
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## Training Procedure |
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### Tokenizer |
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[`tokenizers`](https://github.com/huggingface/tokenizers) ν¨ν€μ§μ `Character BPE tokenizer`λ‘ νμ΅λμμ΅λλ€. |
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### Speeds, Sizes, Times |
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| Model | # of params | Type | # of layers | # of heads | ffn_dim | hidden_dims | |
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|--------------|:----:|:-------:|--------:|--------:|--------:|--------------:| |
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| `KoBART-base` | 124M | Encoder | 6 | 16 | 3072 | 768 | |
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| | | Decoder | 6 | 16 | 3072 | 768 | |
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# Evaluation |
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## Testing Data, Factors & Metrics |
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### Testing Data |
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More information needed |
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### Factors |
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More information needed |
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### Metrics |
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More information needed |
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## Results |
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NSMC |
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- acc. : 0.901 |
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The model authors also note in the [GitHub Repo](https://github.com/haven-jeon/KoBART): |
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| | [NSMC](https://github.com/e9t/nsmc)(acc) | [KorSTS](https://github.com/kakaobrain/KorNLUDatasets)(spearman) | [Question Pair](https://github.com/aisolab/nlp_classification/tree/master/BERT_pairwise_text_classification/qpair)(acc) | |
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|---|---|---|---| |
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| **KoBART-base** | 90.24 | 81.66 | 94.34 | |
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# Model Examination |
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More information needed |
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# Environmental Impact |
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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). |
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- **Hardware Type:** More information needed |
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- **Hours used:** More information needed |
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- **Cloud Provider:** More information needed |
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- **Compute Region:** More information needed |
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- **Carbon Emitted:** More information needed |
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# Technical Specifications [optional] |
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## Model Architecture and Objective |
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More information needed |
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## Compute Infrastructure |
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More information needed |
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### Hardware |
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More information needed |
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### Software |
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More information needed. |
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# Citation |
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**BibTeX:** |
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More information needed. |
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# Glossary [optional] |
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More information needed |
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# More Information [optional] |
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More information needed |
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# Model Card Authors [optional] |
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Heewon(Haven) Jeon in collaboration with Ezi Ozoani and the Hugging Face team |
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# Model Card Contact |
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The model authors note in the [GitHub Repo](https://github.com/haven-jeon/KoBART): |
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`KoBART` κ΄λ ¨ μ΄μλ [μ΄κ³³](https://github.com/SKT-AI/KoBART/issues)μ μ¬λ €μ£ΌμΈμ. |
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# How to Get Started with the Model |
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Use the code below to get started with the model. |
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<details> |
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<summary> Click to expand </summary> |
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```python |
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from transformers import PreTrainedTokenizerFast, BartModel |
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tokenizer = PreTrainedTokenizerFast.from_pretrained('gogamza/kobart-base-v2') |
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model = BartModel.from_pretrained('gogamza/kobart-base-v2') |
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``` |
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</details> |
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