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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: hsohn3/cchs-timebert-visit-uncased-wordlevel-block512-batch4-ep100 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# hsohn3/cchs-timebert-visit-uncased-wordlevel-block512-batch4-ep100 |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.8009 |
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- Epoch: 99 |
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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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- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Epoch | |
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|:----------:|:-----:| |
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| 3.8699 | 0 | |
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| 3.1667 | 1 | |
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| 3.1286 | 2 | |
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| 3.1169 | 3 | |
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| 3.1077 | 4 | |
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| 3.0989 | 5 | |
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| 3.0911 | 6 | |
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| 3.0896 | 7 | |
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| 3.0820 | 8 | |
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| 3.0856 | 9 | |
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| 3.0827 | 10 | |
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| 3.0800 | 11 | |
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| 3.0647 | 12 | |
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| 3.0396 | 13 | |
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| 3.0052 | 14 | |
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| 2.9879 | 15 | |
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| 2.9633 | 16 | |
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| 2.9449 | 17 | |
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| 2.9217 | 18 | |
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| 2.8921 | 19 | |
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| 2.8625 | 20 | |
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| 2.8153 | 21 | |
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| 2.7495 | 22 | |
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| 2.6202 | 23 | |
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| 2.3762 | 24 | |
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| 2.1064 | 25 | |
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| 1.8489 | 26 | |
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| 1.6556 | 27 | |
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| 1.5005 | 28 | |
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| 1.4110 | 29 | |
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| 1.3472 | 30 | |
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| 1.2896 | 31 | |
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| 1.2391 | 32 | |
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| 1.2001 | 33 | |
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| 1.1663 | 34 | |
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| 1.1418 | 35 | |
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| 1.1159 | 36 | |
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| 1.0987 | 37 | |
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| 1.0753 | 38 | |
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| 1.0608 | 39 | |
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| 1.0456 | 40 | |
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| 1.0381 | 41 | |
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| 1.0248 | 42 | |
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| 1.0127 | 43 | |
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| 0.9970 | 44 | |
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| 0.9958 | 45 | |
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| 0.9847 | 46 | |
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| 0.9789 | 47 | |
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| 0.9617 | 48 | |
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| 0.9575 | 49 | |
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| 0.9517 | 50 | |
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| 0.9442 | 51 | |
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| 0.9379 | 52 | |
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| 0.9350 | 53 | |
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| 0.9325 | 54 | |
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| 0.9235 | 55 | |
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| 0.9182 | 56 | |
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| 0.9139 | 57 | |
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| 0.9074 | 58 | |
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| 0.8984 | 59 | |
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| 0.8988 | 60 | |
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| 0.8958 | 61 | |
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| 0.8937 | 62 | |
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| 0.8853 | 63 | |
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| 0.8812 | 64 | |
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| 0.8758 | 65 | |
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| 0.8729 | 66 | |
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| 0.8732 | 67 | |
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| 0.8647 | 68 | |
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| 0.8634 | 69 | |
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| 0.8604 | 70 | |
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| 0.8577 | 71 | |
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| 0.8597 | 72 | |
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| 0.8508 | 73 | |
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| 0.8510 | 74 | |
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| 0.8450 | 75 | |
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| 0.8451 | 76 | |
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| 0.8398 | 77 | |
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| 0.8392 | 78 | |
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| 0.8345 | 79 | |
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| 0.8350 | 80 | |
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| 0.8329 | 81 | |
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| 0.8299 | 82 | |
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| 0.8257 | 83 | |
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| 0.8217 | 84 | |
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| 0.8192 | 85 | |
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| 0.8211 | 86 | |
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| 0.8208 | 87 | |
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| 0.8171 | 88 | |
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| 0.8166 | 89 | |
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| 0.8134 | 90 | |
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| 0.8124 | 91 | |
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| 0.8102 | 92 | |
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| 0.8133 | 93 | |
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| 0.8066 | 94 | |
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| 0.8023 | 95 | |
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| 0.8049 | 96 | |
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| 0.8024 | 97 | |
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| 0.7980 | 98 | |
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| 0.8009 | 99 | |
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### Framework versions |
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- Transformers 4.20.1 |
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- TensorFlow 2.8.2 |
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- Datasets 2.3.2 |
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- Tokenizers 0.12.1 |
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