RoBERTa-legal-de-cased_German_legal_SQuAD_100
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3939
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:
- learning_rate: 2e-05
- train_batch_size: 160
- eval_batch_size: 40
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 2 | 6.2702 |
| No log | 2.0 | 4 | 6.2057 |
| No log | 3.0 | 6 | 6.0590 |
| No log | 4.0 | 8 | 5.8979 |
| No log | 5.0 | 10 | 5.4639 |
| No log | 6.0 | 12 | 5.3637 |
| No log | 7.0 | 14 | 5.1792 |
| No log | 8.0 | 16 | 4.9258 |
| No log | 9.0 | 18 | 4.7628 |
| No log | 10.0 | 20 | 4.5534 |
| No log | 11.0 | 22 | 4.3370 |
| No log | 12.0 | 24 | 4.1347 |
| No log | 13.0 | 26 | 3.9543 |
| No log | 14.0 | 28 | 3.7819 |
| No log | 15.0 | 30 | 3.6555 |
| No log | 16.0 | 32 | 3.5673 |
| No log | 17.0 | 34 | 3.4768 |
| No log | 18.0 | 36 | 3.3835 |
| No log | 19.0 | 38 | 3.3112 |
| No log | 20.0 | 40 | 3.2279 |
| No log | 21.0 | 42 | 3.1581 |
| No log | 22.0 | 44 | 3.0989 |
| No log | 23.0 | 46 | 3.0178 |
| No log | 24.0 | 48 | 2.9702 |
| No log | 25.0 | 50 | 2.9084 |
| No log | 26.0 | 52 | 2.8226 |
| No log | 27.0 | 54 | 2.8405 |
| No log | 28.0 | 56 | 2.8029 |
| No log | 29.0 | 58 | 2.6979 |
| No log | 30.0 | 60 | 2.7140 |
| No log | 31.0 | 62 | 2.6985 |
| No log | 32.0 | 64 | 2.6223 |
| No log | 33.0 | 66 | 2.6349 |
| No log | 34.0 | 68 | 2.5541 |
| No log | 35.0 | 70 | 2.4758 |
| No log | 36.0 | 72 | 2.4601 |
| No log | 37.0 | 74 | 2.4836 |
| No log | 38.0 | 76 | 2.3613 |
| No log | 39.0 | 78 | 2.2917 |
| No log | 40.0 | 80 | 2.3154 |
| No log | 41.0 | 82 | 2.2682 |
| No log | 42.0 | 84 | 2.2784 |
| No log | 43.0 | 86 | 2.2534 |
| No log | 44.0 | 88 | 2.1457 |
| No log | 45.0 | 90 | 2.1808 |
| No log | 46.0 | 92 | 2.2528 |
| No log | 47.0 | 94 | 2.1585 |
| No log | 48.0 | 96 | 2.0309 |
| No log | 49.0 | 98 | 2.0622 |
| No log | 50.0 | 100 | 2.0533 |
| No log | 51.0 | 102 | 1.9610 |
| No log | 52.0 | 104 | 1.9597 |
| No log | 53.0 | 106 | 1.8926 |
| No log | 54.0 | 108 | 1.8149 |
| No log | 55.0 | 110 | 1.7849 |
| No log | 56.0 | 112 | 1.8135 |
| No log | 57.0 | 114 | 1.8190 |
| No log | 58.0 | 116 | 1.8126 |
| No log | 59.0 | 118 | 1.8007 |
| No log | 60.0 | 120 | 1.7200 |
| No log | 61.0 | 122 | 1.6408 |
| No log | 62.0 | 124 | 1.6524 |
| No log | 63.0 | 126 | 1.6697 |
| No log | 64.0 | 128 | 1.6660 |
| No log | 65.0 | 130 | 1.5907 |
| No log | 66.0 | 132 | 1.5765 |
| No log | 67.0 | 134 | 1.5575 |
| No log | 68.0 | 136 | 1.5455 |
| No log | 69.0 | 138 | 1.5267 |
| No log | 70.0 | 140 | 1.4875 |
| No log | 71.0 | 142 | 1.4474 |
| No log | 72.0 | 144 | 1.4436 |
| No log | 73.0 | 146 | 1.4609 |
| No log | 74.0 | 148 | 1.4983 |
| No log | 75.0 | 150 | 1.4903 |
| No log | 76.0 | 152 | 1.4506 |
| No log | 77.0 | 154 | 1.3982 |
| No log | 78.0 | 156 | 1.3735 |
| No log | 79.0 | 158 | 1.3670 |
| No log | 80.0 | 160 | 1.3977 |
| No log | 81.0 | 162 | 1.4478 |
| No log | 82.0 | 164 | 1.4565 |
| No log | 83.0 | 166 | 1.4186 |
| No log | 84.0 | 168 | 1.3839 |
| No log | 85.0 | 170 | 1.3633 |
| No log | 86.0 | 172 | 1.3686 |
| No log | 87.0 | 174 | 1.3873 |
| No log | 88.0 | 176 | 1.3998 |
| No log | 89.0 | 178 | 1.4084 |
| No log | 90.0 | 180 | 1.4076 |
| No log | 91.0 | 182 | 1.3899 |
| No log | 92.0 | 184 | 1.3820 |
| No log | 93.0 | 186 | 1.3821 |
| No log | 94.0 | 188 | 1.3837 |
| No log | 95.0 | 190 | 1.3902 |
| No log | 96.0 | 192 | 1.3930 |
| No log | 97.0 | 194 | 1.3938 |
| No log | 98.0 | 196 | 1.3954 |
| No log | 99.0 | 198 | 1.3950 |
| No log | 100.0 | 200 | 1.3939 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.7
- Tokenizers 0.15.0
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