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Transformerã«ã‚ˆã‚‹æ™‚系列データ予測ã®ã”紹介 - Platinum Data Blog by BrainPad ブレインパッド
本記事ã¯ã€å½“社オウンドメディア「Doorsã€ã«ç§»è»¢ã—ã¾ã—ãŸã€‚ ç´„5秒後ã«è‡ªå‹•çš„ã«ãƒªãƒ€ã‚¤ãƒ¬ã‚¯ãƒˆã—ã¾ã™ã€‚ 発展を続ã‘る「自然言語処ç†ã€æŠ€è¡“。ãã®ä¸ã§ã‚‚幅広ã使用ã•ã‚Œã‚‹æ·±å±¤å¦ç¿’モデルTransformerã¯ã€è‡ªç„¶è¨€èªžå‡¦ç†ä»¥å¤–ã®éŸ³æ¥½ç”Ÿæˆã‚„物体検出ãªã©ã®é ˜åŸŸã§ã‚‚é©ç”¨ã§ãã¾ã™ã€‚本ブãƒã‚°ã§ã¯ã€ Transformerを時系列データã«é©ç”¨ã™ã‚‹æ–¹æ³•ã‚’ã”紹介ã—ã¾ã™ã€‚ ã“ã‚“ã«ã¡ã¯ã€AIソリューションサービス部ã®äº•å‡ºã¨ç”³ã—ã¾ã™ã€‚ ã“ã®è¨˜äº‹ã§ã¯ã€ç‰¹ã«è‡ªç„¶è¨€èªžå‡¦ç†åˆ†é‡Žã§å¹…広ã使用ã•ã‚Œã‚‹æ·±å±¤å¦ç¿’モデルTransformerを時系列データã¸é©ç”¨ã™ã‚‹æ–¹æ³•ã«é–¢ã—ã¦ã”紹介ã—ã¾ã™ã€‚ 以å‰ã®è¨˜äº‹ã§ã¯ã€Transformerã®æ§‹é€ や特徴ãªã©ã«ã¤ã„ã¦ã€è‡ªç„¶è¨€èªžå‡¦ç†åˆ†é‡Žã®æ©Ÿæ¢°ç¿»è¨³ã‚’例ã¨ã—ã¦ã”紹介ã—ã¦ãŠã‚Šã¾ã™ã€‚ã¯ã˜ã‚ã«ã€ã“ã¡ã‚‰ã®è¨˜äº‹ã‚’ã”一èªã—ã¦ã„ãŸã ãã“ã¨ã§ã€ã‚ˆã‚Šæœ¬è¨˜äº‹ã§ã”紹介ã™ã‚‹å†…容ã«å¯¾ã™ã‚‹ç†è§£ãŒæ·±ã¾ã‚‹ã‹ã¨æ€ã„ã¾ã™ã€‚ Transform
Recent Advances in Language Model Fine-tuning
Recent Advances in Language Model Fine-tuning This article provides an overview of recent methods to fine-tune large pre-trained language models. Fine-tuning a pre-trained language model (LM) has become the de facto standard for doing transfer learning in natural language processing. Over the last three years (Ruder, 2018), fine-tuning (Howard & Ruder, 2018) has superseded the use of feature extra
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Algorithms for Decision Making
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