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hsohn3/cchs-bert-visit-uncased-wordlevel-block512-batch4-ep100
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.7195
- 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 |
---|---|
3.8730 | 0 |
3.0562 | 1 |
3.0168 | 2 |
3.0032 | 3 |
2.9954 | 4 |
2.9951 | 5 |
2.9904 | 6 |
2.9765 | 7 |
2.9788 | 8 |
2.9692 | 9 |
2.9656 | 10 |
2.9761 | 11 |
2.9643 | 12 |
2.9393 | 13 |
2.9026 | 14 |
2.8685 | 15 |
2.8438 | 16 |
2.8279 | 17 |
2.8107 | 18 |
2.7896 | 19 |
2.7716 | 20 |
2.7458 | 21 |
2.7118 | 22 |
2.6519 | 23 |
2.5933 | 24 |
2.4702 | 25 |
2.2842 | 26 |
2.0712 | 27 |
1.8406 | 28 |
1.6374 | 29 |
1.4836 | 30 |
1.3824 | 31 |
1.3079 | 32 |
1.2538 | 33 |
1.2054 | 34 |
1.1700 | 35 |
1.1432 | 36 |
1.1122 | 37 |
1.0939 | 38 |
1.0645 | 39 |
1.0465 | 40 |
1.0248 | 41 |
1.0069 | 42 |
0.9902 | 43 |
0.9769 | 44 |
0.9510 | 45 |
0.9394 | 46 |
0.9316 | 47 |
0.9181 | 48 |
0.9090 | 49 |
0.9010 | 50 |
0.8934 | 51 |
0.8791 | 52 |
0.8759 | 53 |
0.8652 | 54 |
0.8566 | 55 |
0.8511 | 56 |
0.8414 | 57 |
0.8373 | 58 |
0.8302 | 59 |
0.8241 | 60 |
0.8246 | 61 |
0.8207 | 62 |
0.8110 | 63 |
0.8081 | 64 |
0.8010 | 65 |
0.7995 | 66 |
0.7965 | 67 |
0.7941 | 68 |
0.7849 | 69 |
0.7866 | 70 |
0.7874 | 71 |
0.7796 | 72 |
0.7742 | 73 |
0.7706 | 74 |
0.7687 | 75 |
0.7686 | 76 |
0.7663 | 77 |
0.7586 | 78 |
0.7554 | 79 |
0.7563 | 80 |
0.7541 | 81 |
0.7527 | 82 |
0.7482 | 83 |
0.7460 | 84 |
0.7436 | 85 |
0.7423 | 86 |
0.7422 | 87 |
0.7385 | 88 |
0.7367 | 89 |
0.7321 | 90 |
0.7320 | 91 |
0.7354 | 92 |
0.7271 | 93 |
0.7270 | 94 |
0.7210 | 95 |
0.7236 | 96 |
0.7263 | 97 |
0.7237 | 98 |
0.7195 | 99 |
Framework versions
- Transformers 4.20.1
- TensorFlow 2.8.2
- Datasets 2.3.2
- Tokenizers 0.12.1