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0_511_513.mp3
越 接 近 越 好
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67.718781
0_513_513.mp3
所 以 我 們 呢
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68.346969
0_513_518.mp3
把 θi 跟 θ 上 標 b 下 標 i 相 減
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68.34765
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68.440496
0_518_519.mp3
然 後 取 它 們 的 平 方
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66.647456
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67.340221
0_520_521.mp3
那 我 們 在 前 面 呢
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69.024642
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69.472001
0_521_524.mp3
會 乘 上 一 個 數 值 叫 做 bi
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67.597155
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67.670833
0_524_526.mp3
這 個 bi 就 是 要 告 訴 我 們 說
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70.209147
0_526_529.mp3
到 底 我 們 有 多 強 烈 地 希 望
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0_529_533.mp3
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67.010031
0_533_534.mp3
越 靠 近 越 好
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69.193448
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69.594312
0_534_536.mp3
如 果 bi 的 值 很 大
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67.397443
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68.752255
0_536_539.mp3
就 代 表 說 我 們 希 望 θi 跟 θbi 非 常 靠 近
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66.252933
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67.326163
0_539_541.mp3
如 果 bi 的 值 很 小
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69.413707
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70.832307
0_541_545.mp3
代 表 我 們 覺 得 θi 沒 有 跟 θbi 很 靠 近
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61.264788
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61.93316
0_545_546.mp3
也 無 所 謂
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67.856958
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67.850412
0_547_548.mp3
好 那 這 個 呢
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62.529196
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62.65228
0_548_550.mp3
就 是 我 們 要 optimize
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71.459684
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71.459684
0_550_551.mp3
這 個 l' 呢
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69.588177
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69.588177
0_551_553.mp3
就 是 我 們 真 正 要 optimize 的 對 象
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68.800768
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68.809427
0_553_555.mp3
它 裡 面 有 兩 項
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69.385889
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69.389408
0_555_557.mp3
一 個 是 原 來 的 新 的 任 務 的 loss
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70.044672
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70.640349
0_557_558.mp3
另 外 一 項 呢
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69.725326
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70.410722
0_558_562.mp3
就 是 要 讓 θi 跟 θbi 越 接 近 越 好
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62.120356
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62.42401
0_562_564.mp3
但 是 要 注 意 一 下
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69.702739
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69.941739
0_564_565.mp3
我 們 並 不 是
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67.984912
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68.417512
0_566_568.mp3
平 等 地 去 看 待
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69.536538
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70.371199
0_568_571.mp3
所 有 的 參 數 要 不 要 接 近 這 件 事
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67.430058
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67.86886
0_571_575.mp3
我 們 其 實 只 要 求 θ 跟 θbi
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71.149032
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71.399767
0_575_577.mp3
在 某 些 參 數 上 接 近 就 好
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67.845854
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67.89834
0_577_580.mp3
並 不 需 要 所 有 參 數 都 接 近
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69.855449
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70.518701
0_580_582.mp3
只 要 某 些 參 數 接 近 就 好
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68.533277
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68.753175
0_582_584.mp3
那 哪 些 參 數 要 接 近
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71.099962
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71.568207
0_584_586.mp3
就 由 bi 來 控 制
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68.661499
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68.970752
0_586_587.mp3
如 果 某 一 個 參 數 i
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69.344787
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69.458712
0_587_589.mp3
第 i 個 參 數 它 的 bi 很 大
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68.254007
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68.277336
0_589_591.mp3
就 代 表 我 們 希 望 第 i 個 參 數
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69.107761
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69.804874
0_591_593.mp3
它 跟 舊 的 參 數
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70.445448
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70.48104
0_593_594.mp3
之 前 的 任 務 learn 出 來 的 那 個 參 數
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67.279153
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67.775908
0_594_595.mp3
要 非 常 接 近
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70.418662
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70.911697
0_595_597.mp3
反 之 bi 等 於 0 就 代 表
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69.944078
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70.009222
0_597_599.mp3
我 們 根 本 不 care 新 的 參 數 跟 舊 的 參 數
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69.39682
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70.18407
0_599_601.mp3
到 底 要 不 要 接 近
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68.898494
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69.768087
0_602_604.mp3
好 所 以 如 果 今 天 呢
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68.915591
0_604_605.mp3
bi 設 為 0
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68.927929
0_605_607.mp3
所 有 的 參 數 它 的 i
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70.347326
0_607_610.mp3
所 有 的 參 數 它 的 bi 我 們 都 設 為 0
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66.121371
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66.421799
0_610_611.mp3
那 意 味 著 什 麼
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70.002742
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70.580015
0_611_612.mp3
那 意 味 著 就 是
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69.838059
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70.209691
0_612_616.mp3
我 們 沒 有 給 我 們 的 θi 任 何 限 制
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62.556636
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62.719653
0_616_619.mp3
我 們 完 全 沒 有 要 求 新 的 learn 出 來 的 參 數
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66.826527
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67.342898
0_619_623.mp3
跟 過 去 學 出 來 的 參 數 有 什 麼 樣 的 關 係
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69.279677
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69.464083
0_623_625.mp3
那 這 個 時 候 就 是 一 般 的 training
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68.052055
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68.277981
0_625_628.mp3
就 會 有 catastrophic forgetting 的 問 題
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63.758233
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64.135391
0_628_631.mp3
但 是 你 可 能 會 想 說 既 然 bi 設 0 是 不 好 的
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69.05288
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69.122065
0_631_634.mp3
那 我 們 就 把 bi 給 它 設 一 個 非 常 大 的 值
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35.52337
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35.615288
0_634_636.mp3
所 有 的 i
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68.082024
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68.089948
0_636_639.mp3
所 有 的 參 數 都 給 它 一 個 非 常 大 的 bi
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57.432351
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57.072254
0_639_641.mp3
那 這 樣 就 不 會 有 forgetting 的 問 題
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67.305672
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68.130737
0_641_643.mp3
但 是 你 會 進 入 另 外 一 個 極 端
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66.599539
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66.383572
0_643_646.mp3
這 個 極 端 叫 做 intransigence
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69.412426
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70.477234
0_646_648.mp3
這 個 極 這 個 intransigence 的 意 思 就 是
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63.184203
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63.242116
0_648_651.mp3
這 個 不 肯 妥 協 不 肯 讓 步
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58.219395
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58.068755
0_651_653.mp3
頑 固 的 意 思
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65.250736
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66.173507
0_653_656.mp3
所 以 intransigence 的 意 思 是 說
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66.740746
0_656_658.mp3
假 設 你 現 在 bi 非 常 地
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68.44458
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70.055016
0_658_659.mp3
非 常 地 大
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68.691784
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69.369939
0_659_661.mp3
那 你 最 後 learn 出 來 的 結 果
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69.822796
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69.998747
0_661_664.mp3
θi 跟 θb 就 會 非 常 地 接 近
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63.119446
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64.362151
0_664_667.mp3
你 的 新 的 參 數 跟 舊 的 參 數 會 非 常 接 近
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67.408517
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68.615155
0_667_668.mp3
那 你 的 模 型
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69.834016
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70.523004
0_668_670.mp3
可 能 在 舊 的 任 務 上 不 會 遺 忘
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68.83702
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69.424628
0_670_672.mp3
但 新 的 任 務 它 學 不 好
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68.911539
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69.289114
0_672_674.mp3
它 沒 有 能 力 去 把 新 的 任 務 學 好
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67.474181
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67.441422
0_674_677.mp3
那 這 種 狀 況 就 叫 做 intransigence
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61.587415
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62.008895
0_678_679.mp3
好 講 到 這 邊
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67.542836
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67.578081
0_679_681.mp3
我 們 來 看 一 下 有 沒 有 同 學 有 問 題 要 問 的
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51.310477
0_688_690.mp3
好 有 同 學 說
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65.251491
0_690_691.mp3
聲 音 還 是 炸
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65.122367
0_691_693.mp3
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67.007399
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13.979773
0_698_700.mp3
好 有 同 學 問 說
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63.86526
0_700_703.mp3
bi 是 要 人 為 設 定
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58.245251
0_703_709.mp3
還 是 可 以 作 為 參 數 的 一 部 分 給 機 器 訓 練
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68.182051
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68.896828
0_709_711.mp3
好 那 再 等 一 下
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69.13943
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69.204831
0_711_712.mp3
在 文 獻 上
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64.974019
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66.510423
0_712_716.mp3
這 個 bi 都 是 人 為 設 定 的
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67.839493
0_716_718.mp3
在 lifelong learning 的 研 究 裡 面
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67.330268
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68.322453
0_718_720.mp3
關 鍵 的 技 術 就 在 於
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69.303185
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69.777224
0_720_723.mp3
我 們 怎 麼 設 定 這 個 bi
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37.961618
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36.475059
0_723_726.mp3
那 如 果 bi 用 learn 的 到 底 行 不 行 呢
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67.408448
0_726_728.mp3
你 可 以 想 見 說 在 這 個 任 務 裡 面
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11.935437
0_728_731.mp3
你 恐 怕 不 能 讓 bi 用 learn 的
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67.179215
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67.78382
0_731_733.mp3
如 果 你 讓 bi 自 己 學
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66.225733
0_733_734.mp3
它 會 學 出 什 麼
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68.086768
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68.995798
0_734_737.mp3
對 它 來 說 它 要 讓 loss 越 小 越 好 嘛
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64.706643
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65.345756
0_737_738.mp3
那 怎 麼 讓 loss 最 小
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67.813157
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67.84641
0_738_739.mp3
直 接 bi 等 於 0
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34.560486
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33.916294
0_739_740.mp3
loss 就 最 小 了
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68.670021
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68.930207
0_740_743.mp3
所 以 如 果 你 讓 bi 直 接 用 learn 的
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69.755758
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69.989129
0_743_745.mp3
你 並 沒 有 辦 法 達 到 lifelong learning 的 效 果
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