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README.md
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@@ -50,19 +50,19 @@ model = AutoModel.from_pretrained("nlpaueb/sec-bert-base")
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## Use LEBAL-BERT variants as Language Models
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| Model | Masked token | Predictions |
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| ---------------------------------- | ------------ | ------------ |
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| Total net sales [MASK] 2% or $5.4 billion during 2019 compared to 2018.
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| **BERT-BASE-UNCASED** | decreased | increased
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| **SEC-BERT-BASE** | decreased |
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| **SEC-BERT-NUM** | decreased |
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| **SEC-BERT-SHAPE** | decreased |
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| Total net sales decreased 2% or $5.4 [MASK] during 2019 compared to 2018.
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| **BERT-BASE-UNCASED** | billion |
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| **SEC-BERT-BASE** | billion |
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| **SEC-BERT-NUM** | billion |
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| **SEC-BERT-SHAPE** | billion |
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| During 2019, the Company [MASK] $67.1 billion of its common stock and paid dividend equivalents of $14.1 billion.
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| **BERT-BASE-UNCASED** | repurchased | ('letter', '0.38'), ('dealer', '0.04'), ('employment', '0.03'), ('award', '0.03'), ('contribution', '0.02')
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## Use LEBAL-BERT variants as Language Models
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| Model | Masked token | Predictions (Probability) |
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| ---------------------------------- | ------------ | ------------ |
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| Total net sales [MASK] 2% or $5.4 billion during 2019 compared to 2018.
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| **BERT-BASE-UNCASED** | decreased | increased (0.221), were (0.131), are (0.103), rose (0.075), of (0.058)
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| **SEC-BERT-BASE** | decreased | increased (0.678), decreased (0.282), declined (0.017), grew (0.016), rose (0.004)
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| **SEC-BERT-NUM** | decreased | increased (0.665), decreased (0.281), grew (0.028), declined (0.015), rose (0.008)
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| **SEC-BERT-SHAPE** | decreased | increased (0.793), decreased (0.145), grew (0.042), declined (0.011), rose (0.003)
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| Total net sales decreased 2% or $5.4 [MASK] during 2019 compared to 2018.
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+
| **BERT-BASE-UNCASED** | billion |
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+
| **SEC-BERT-BASE** | billion |
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+
| **SEC-BERT-NUM** | billion |
|
65 |
+
| **SEC-BERT-SHAPE** | billion |
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| | |
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| During 2019, the Company [MASK] $67.1 billion of its common stock and paid dividend equivalents of $14.1 billion.
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| **BERT-BASE-UNCASED** | repurchased | ('letter', '0.38'), ('dealer', '0.04'), ('employment', '0.03'), ('award', '0.03'), ('contribution', '0.02')
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