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pretrained-m-bert-100
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 5.7003
- Validation Loss: 15.3566
- 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': 'Adam', 'learning_rate': 1e-04, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32
Training results
| Train Loss | Validation Loss | Epoch |
|---|---|---|
| 10.2669 | 10.9400 | 0 |
| 7.8880 | 10.8967 | 1 |
| 6.8580 | 11.5024 | 2 |
| 6.4321 | 11.5023 | 3 |
| 6.2235 | 11.2212 | 4 |
| 6.0038 | 11.3128 | 5 |
| 5.9881 | 11.3604 | 6 |
| 5.4409 | 11.6872 | 7 |
| 5.2113 | 11.5379 | 8 |
| 5.2660 | 12.0264 | 9 |
| 5.2330 | 11.7627 | 10 |
| 5.1121 | 12.2919 | 11 |
| 5.2126 | 12.6272 | 12 |
| 5.2086 | 11.3478 | 13 |
| 5.2459 | 12.2183 | 14 |
| 5.0035 | 11.7580 | 15 |
| 4.9613 | 12.4852 | 16 |
| 5.0312 | 12.4627 | 17 |
| 5.0073 | 13.6309 | 18 |
| 5.4284 | 12.7799 | 19 |
| 5.3100 | 12.6417 | 20 |
| 5.0765 | 12.7851 | 21 |
| 5.2276 | 13.3828 | 22 |
| 5.1986 | 12.7421 | 23 |
| 4.8935 | 12.8679 | 24 |
| 4.6959 | 12.9201 | 25 |
| 5.4161 | 13.4416 | 26 |
| 5.2459 | 14.0112 | 27 |
| 5.2781 | 13.2740 | 28 |
| 5.5104 | 12.8646 | 29 |
| 5.5024 | 13.7514 | 30 |
| 5.6284 | 13.7125 | 31 |
| 5.8452 | 13.6332 | 32 |
| 5.5767 | 13.8019 | 33 |
| 5.6444 | 13.4279 | 34 |
| 5.5551 | 13.2666 | 35 |
| 5.5421 | 13.5996 | 36 |
| 5.5246 | 13.1686 | 37 |
| 5.5233 | 13.3788 | 38 |
| 5.6011 | 13.4038 | 39 |
| 5.3695 | 13.5241 | 40 |
| 5.5061 | 13.6035 | 41 |
| 5.4534 | 13.8652 | 42 |
| 5.4222 | 13.4525 | 43 |
| 5.4408 | 13.6572 | 44 |
| 5.6683 | 13.7671 | 45 |
| 5.7137 | 14.1255 | 46 |
| 5.6777 | 14.4026 | 47 |
| 5.6776 | 14.3435 | 48 |
| 5.8337 | 14.3650 | 49 |
| 5.8583 | 14.2897 | 50 |
| 5.6849 | 14.6518 | 51 |
| 5.7112 | 14.5420 | 52 |
| 5.7281 | 13.9947 | 53 |
| 5.9154 | 14.3210 | 54 |
| 5.6742 | 13.8867 | 55 |
| 5.8674 | 14.2819 | 56 |
| 5.7128 | 14.5811 | 57 |
| 5.7091 | 14.2113 | 58 |
| 5.7479 | 14.4418 | 59 |
| 5.7632 | 13.9566 | 60 |
| 5.6443 | 14.1394 | 61 |
| 5.6794 | 14.5981 | 62 |
| 5.6450 | 14.5139 | 63 |
| 5.6935 | 14.3309 | 64 |
| 5.7443 | 14.3540 | 65 |
| 5.7014 | 14.7472 | 66 |
| 5.7407 | 14.4245 | 67 |
| 5.9023 | 14.4602 | 68 |
| 5.9222 | 14.6654 | 69 |
| 5.6813 | 14.3179 | 70 |
| 5.6505 | 14.1670 | 71 |
| 5.8407 | 14.2520 | 72 |
| 5.6683 | 14.1696 | 73 |
| 5.6880 | 15.1198 | 74 |
| 5.8254 | 14.2783 | 75 |
| 5.7758 | 14.5934 | 76 |
| 5.7180 | 14.4779 | 77 |
| 5.7348 | 14.3955 | 78 |
| 5.6680 | 14.0637 | 79 |
| 5.7029 | 14.6120 | 80 |
| 5.7088 | 14.3396 | 81 |
| 5.7215 | 14.5878 | 82 |
| 5.5987 | 15.0465 | 83 |
| 5.7613 | 14.7521 | 84 |
| 5.7670 | 14.9828 | 85 |
| 5.7954 | 14.6714 | 86 |
| 5.6080 | 15.2686 | 87 |
| 5.7493 | 14.8772 | 88 |
| 5.6884 | 14.4567 | 89 |
| 5.6932 | 14.3316 | 90 |
| 5.7152 | 15.2725 | 91 |
| 5.6548 | 15.0855 | 92 |
| 5.6196 | 14.8487 | 93 |
| 5.7889 | 14.7169 | 94 |
| 5.5958 | 14.9320 | 95 |
| 5.7047 | 14.8829 | 96 |
| 5.5637 | 14.8704 | 97 |
| 5.6375 | 14.7917 | 98 |
| 5.7003 | 15.3566 | 99 |
Framework versions
- Transformers 4.27.0.dev0
- TensorFlow 2.9.2
- Datasets 2.9.0
- Tokenizers 0.13.2
