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--- |
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license: apache-2.0 |
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widget: |
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- text: >- |
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translate_ko2en: IBM 왓슨X는 AI 및 데이터 플랫폼이다. 신뢰할 수 있는 데이터, 속도, 거버넌스를 갖고 파운데이션 |
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모델 및 머신 러닝 기능을 포함한 AI 모델을 학습시키고, 조정해, 조직 전체에서 활용하기 위한 전 과정을 아우르는 기술과 서비스를 |
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제공한다. |
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example_title: KO2EN 1 |
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- text: >- |
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translate_ko2en: 이용자는 신뢰할 수 있고 개방된 환경에서 자신의 데이터에 대해 자체적인 AI를 구축하거나, 시장에 출시된 |
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AI 모델을 정교하게 조정할 수 있다. 대규모로 활용하기 위한 도구 세트, 기술, 인프라 및 전문 컨설팅 서비스를 활용할 수 있다. |
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example_title: KO2EN 2 |
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- text: >- |
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translate_en2ko: The Seoul Metropolitan Government said Wednesday that it |
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would develop an AI-based congestion monitoring system to provide better |
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information to passengers about crowd density at each subway station. |
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example_title: EN2KO 1 |
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- text: >- |
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translate_en2ko: According to Seoul Metro, the operator of the subway |
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service in Seoul, the new service will help analyze the real-time flow of |
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passengers and crowd levels in subway compartments, improving operational |
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efficiency. |
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example_title: EN2KO 2 |
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language: |
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- ko |
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- en |
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pipeline_tag: translation |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# ko2en_bidirection |
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This model is a fine-tuned version of [KETI-AIR/long-ke-t5-base](https://huggingface.co/KETI-AIR/long-ke-t5-base) on the csv_dataset.py dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6808 |
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- Bleu: 52.2152 |
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- Gen Len: 396.0215 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.001 |
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- train_batch_size: 8 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- total_train_batch_size: 64 |
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- total_eval_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 1.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |
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|:-------------:|:-----:|:------:|:---------------:|:----:|:-------:| |
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| 0.5962 | 1.0 | 750093 | 0.6808 | 0.0 | 18.369 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 1.13.0 |
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- Datasets 2.9.0 |
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- Tokenizers 0.13.2 |
