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--- |
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library_name: transformers |
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license: mit |
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base_model: indolem/indobert-base-uncased |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: Labira/LabiraPJOK_1_500 |
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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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# Labira/LabiraPJOK_1_500 |
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This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-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: 0.0005 |
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- Validation Loss: 7.9553 |
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- Epoch: 137 |
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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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 1500, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Validation Loss | Epoch | |
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|:----------:|:---------------:|:-----:| |
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| 0.0054 | 8.3302 | 0 | |
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| 0.0108 | 7.8442 | 1 | |
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| 0.0114 | 7.0958 | 2 | |
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| 0.0284 | 6.6490 | 3 | |
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| 0.0179 | 7.3034 | 4 | |
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| 0.0044 | 8.1785 | 5 | |
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| 0.0070 | 8.4039 | 6 | |
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| 0.0038 | 8.2728 | 7 | |
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| 0.0028 | 8.1154 | 8 | |
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| 0.0140 | 8.1207 | 9 | |
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| 0.0160 | 8.1384 | 10 | |
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| 0.0029 | 8.2978 | 11 | |
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| 0.0112 | 8.6940 | 12 | |
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| 0.0100 | 8.7433 | 13 | |
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| 0.0062 | 8.6486 | 14 | |
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| 0.0059 | 8.4821 | 15 | |
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| 0.0055 | 8.4559 | 16 | |
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| 0.0039 | 8.5136 | 17 | |
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| 0.0044 | 8.2783 | 18 | |
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| 0.0016 | 8.0974 | 19 | |
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| 0.0094 | 7.9739 | 20 | |
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| 0.0020 | 8.2513 | 21 | |
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| 0.0008 | 8.4637 | 22 | |
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| 0.0039 | 8.2813 | 23 | |
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| 0.0017 | 8.2027 | 24 | |
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| 0.0018 | 8.2722 | 25 | |
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| 0.0015 | 8.3875 | 26 | |
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| 0.0013 | 8.4975 | 27 | |
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| 0.0013 | 8.6171 | 28 | |
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| 0.0009 | 8.7272 | 29 | |
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| 0.0010 | 8.8335 | 30 | |
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| 0.0007 | 8.9168 | 31 | |
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| 0.0007 | 8.9992 | 32 | |
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| 0.0006 | 9.0661 | 33 | |
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| 0.0007 | 9.1103 | 34 | |
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| 0.0004 | 9.1424 | 35 | |
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| 0.0008 | 9.1573 | 36 | |
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| 0.0006 | 9.1666 | 37 | |
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| 0.0008 | 9.1732 | 38 | |
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| 0.0004 | 9.1781 | 39 | |
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| 0.0006 | 9.1867 | 40 | |
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| 0.0005 | 9.1986 | 41 | |
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| 0.0005 | 9.2203 | 42 | |
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| 0.0005 | 9.2512 | 43 | |
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| 0.0006 | 9.2889 | 44 | |
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| 0.0005 | 9.3360 | 45 | |
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| 0.0007 | 9.3759 | 46 | |
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| 0.0004 | 9.4144 | 47 | |
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| 0.0006 | 9.4461 | 48 | |
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| 0.0004 | 9.4718 | 49 | |
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| 0.0005 | 9.5113 | 50 | |
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| 0.0004 | 9.5425 | 51 | |
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| 0.0003 | 9.5667 | 52 | |
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| 0.0015 | 9.5468 | 53 | |
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| 0.0003 | 9.4515 | 54 | |
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| 0.0005 | 9.3881 | 55 | |
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| 0.0006 | 9.3797 | 56 | |
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| 0.0006 | 9.3887 | 57 | |
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| 0.0003 | 9.4038 | 58 | |
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| 0.0004 | 9.4206 | 59 | |
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| 0.0003 | 9.4417 | 60 | |
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| 0.0003 | 9.4627 | 61 | |
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| 0.0003 | 9.4775 | 62 | |
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| 0.0004 | 9.4930 | 63 | |
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| 0.0009 | 9.5593 | 64 | |
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| 0.0003 | 9.6068 | 65 | |
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| 0.0003 | 9.6416 | 66 | |
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| 0.0003 | 9.6715 | 67 | |
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| 0.0003 | 9.6956 | 68 | |
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| 0.0004 | 9.7146 | 69 | |
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| 0.0010 | 9.7344 | 70 | |
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| 0.0002 | 9.7946 | 71 | |
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| 0.0003 | 9.7965 | 72 | |
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| 0.0034 | 9.7113 | 73 | |
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| 0.0004 | 9.5730 | 74 | |
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| 0.0005 | 9.4858 | 75 | |
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| 0.0009 | 9.5826 | 76 | |
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| 0.0006 | 9.6923 | 77 | |
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| 0.0005 | 9.8243 | 78 | |
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| 0.0005 | 9.9368 | 79 | |
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| 0.0007 | 10.0514 | 80 | |
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| 0.0006 | 10.1386 | 81 | |
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| 0.0010 | 10.1427 | 82 | |
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| 0.0005 | 9.9261 | 83 | |
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| 0.0011 | 9.8122 | 84 | |
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| 0.0003 | 9.8724 | 85 | |
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| 0.0081 | 9.5494 | 86 | |
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| 0.0151 | 8.3043 | 87 | |
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| 0.0425 | 9.1449 | 88 | |
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| 0.0076 | 8.8560 | 89 | |
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| 0.0113 | 8.2403 | 90 | |
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| 0.0446 | 7.5457 | 91 | |
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| 0.0264 | 7.4204 | 92 | |
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| 0.1545 | 8.0820 | 93 | |
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| 0.3878 | 8.2238 | 94 | |
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| 0.4155 | 6.1718 | 95 | |
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| 0.0410 | 5.0625 | 96 | |
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| 0.0768 | 4.8214 | 97 | |
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| 0.0514 | 4.8477 | 98 | |
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| 0.0150 | 5.2002 | 99 | |
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| 0.0328 | 5.6224 | 100 | |
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| 0.0260 | 5.9887 | 101 | |
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| 0.0040 | 6.2793 | 102 | |
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| 0.0076 | 6.3696 | 103 | |
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| 0.0013 | 6.3642 | 104 | |
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| 0.0075 | 6.4379 | 105 | |
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| 0.0015 | 6.6379 | 106 | |
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| 0.0010 | 6.7736 | 107 | |
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| 0.0023 | 6.8582 | 108 | |
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| 0.0056 | 6.8884 | 109 | |
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| 0.0011 | 6.9125 | 110 | |
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| 0.0014 | 6.9437 | 111 | |
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| 0.0014 | 6.9807 | 112 | |
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| 0.0010 | 7.0239 | 113 | |
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| 0.0006 | 7.0602 | 114 | |
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| 0.0006 | 7.0919 | 115 | |
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| 0.0005 | 7.1213 | 116 | |
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| 0.0008 | 7.1457 | 117 | |
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| 0.0006 | 7.1679 | 118 | |
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| 0.0009 | 7.1871 | 119 | |
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| 0.0288 | 7.3166 | 120 | |
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| 0.0007 | 7.1397 | 121 | |
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| 0.0033 | 6.9025 | 122 | |
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| 0.0020 | 6.8509 | 123 | |
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| 0.0068 | 6.9533 | 124 | |
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| 0.0066 | 7.2446 | 125 | |
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| 0.0035 | 7.5351 | 126 | |
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| 0.0019 | 7.7354 | 127 | |
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| 0.0021 | 7.8376 | 128 | |
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| 0.0007 | 7.9071 | 129 | |
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| 0.0012 | 7.9566 | 130 | |
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| 0.0009 | 8.0014 | 131 | |
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| 0.0013 | 8.0186 | 132 | |
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| 0.0015 | 8.0123 | 133 | |
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| 0.0009 | 7.9870 | 134 | |
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| 0.0008 | 7.9685 | 135 | |
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| 0.0005 | 7.9599 | 136 | |
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| 0.0005 | 7.9553 | 137 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- TensorFlow 2.17.0 |
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- Datasets 3.0.1 |
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- Tokenizers 0.19.1 |
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