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