GQA_RoBERTa_legal_SQuAD_complete_augmented_100
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8115
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: 128
- eval_batch_size: 32
- 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 | 4 | 3.7779 |
No log | 2.0 | 8 | 3.1298 |
No log | 3.0 | 12 | 2.7509 |
No log | 4.0 | 16 | 2.4195 |
No log | 5.0 | 20 | 2.0781 |
No log | 6.0 | 24 | 1.9657 |
No log | 7.0 | 28 | 1.7131 |
No log | 8.0 | 32 | 1.5142 |
No log | 9.0 | 36 | 1.4133 |
No log | 10.0 | 40 | 1.2182 |
No log | 11.0 | 44 | 1.1278 |
No log | 12.0 | 48 | 0.9984 |
No log | 13.0 | 52 | 0.9583 |
No log | 14.0 | 56 | 0.9222 |
No log | 15.0 | 60 | 0.9156 |
No log | 16.0 | 64 | 0.7979 |
No log | 17.0 | 68 | 0.8205 |
No log | 18.0 | 72 | 0.7654 |
No log | 19.0 | 76 | 0.7767 |
No log | 20.0 | 80 | 0.7633 |
No log | 21.0 | 84 | 0.7075 |
No log | 22.0 | 88 | 0.7287 |
No log | 23.0 | 92 | 0.7088 |
No log | 24.0 | 96 | 0.7165 |
No log | 25.0 | 100 | 0.7375 |
No log | 26.0 | 104 | 0.7581 |
No log | 27.0 | 108 | 0.7481 |
No log | 28.0 | 112 | 0.7394 |
No log | 29.0 | 116 | 0.7362 |
No log | 30.0 | 120 | 0.7300 |
No log | 31.0 | 124 | 0.7306 |
No log | 32.0 | 128 | 0.7348 |
No log | 33.0 | 132 | 0.7495 |
No log | 34.0 | 136 | 0.7526 |
No log | 35.0 | 140 | 0.7432 |
No log | 36.0 | 144 | 0.7492 |
No log | 37.0 | 148 | 0.7356 |
No log | 38.0 | 152 | 0.7347 |
No log | 39.0 | 156 | 0.7415 |
No log | 40.0 | 160 | 0.7401 |
No log | 41.0 | 164 | 0.7340 |
No log | 42.0 | 168 | 0.7388 |
No log | 43.0 | 172 | 0.7358 |
No log | 44.0 | 176 | 0.7471 |
No log | 45.0 | 180 | 0.7642 |
No log | 46.0 | 184 | 0.7823 |
No log | 47.0 | 188 | 0.7659 |
No log | 48.0 | 192 | 0.7476 |
No log | 49.0 | 196 | 0.7545 |
No log | 50.0 | 200 | 0.7568 |
No log | 51.0 | 204 | 0.7658 |
No log | 52.0 | 208 | 0.7750 |
No log | 53.0 | 212 | 0.7738 |
No log | 54.0 | 216 | 0.7714 |
No log | 55.0 | 220 | 0.7765 |
No log | 56.0 | 224 | 0.7865 |
No log | 57.0 | 228 | 0.7902 |
No log | 58.0 | 232 | 0.7816 |
No log | 59.0 | 236 | 0.7863 |
No log | 60.0 | 240 | 0.7992 |
No log | 61.0 | 244 | 0.8242 |
No log | 62.0 | 248 | 0.8399 |
No log | 63.0 | 252 | 0.8415 |
No log | 64.0 | 256 | 0.8285 |
No log | 65.0 | 260 | 0.8209 |
No log | 66.0 | 264 | 0.8182 |
No log | 67.0 | 268 | 0.8241 |
No log | 68.0 | 272 | 0.8260 |
No log | 69.0 | 276 | 0.8195 |
No log | 70.0 | 280 | 0.8186 |
No log | 71.0 | 284 | 0.8180 |
No log | 72.0 | 288 | 0.8138 |
No log | 73.0 | 292 | 0.8066 |
No log | 74.0 | 296 | 0.8007 |
No log | 75.0 | 300 | 0.7992 |
No log | 76.0 | 304 | 0.8054 |
No log | 77.0 | 308 | 0.8121 |
No log | 78.0 | 312 | 0.8173 |
No log | 79.0 | 316 | 0.8279 |
No log | 80.0 | 320 | 0.8365 |
No log | 81.0 | 324 | 0.8280 |
No log | 82.0 | 328 | 0.8165 |
No log | 83.0 | 332 | 0.8094 |
No log | 84.0 | 336 | 0.8064 |
No log | 85.0 | 340 | 0.8037 |
No log | 86.0 | 344 | 0.8060 |
No log | 87.0 | 348 | 0.8084 |
No log | 88.0 | 352 | 0.8112 |
No log | 89.0 | 356 | 0.8121 |
No log | 90.0 | 360 | 0.8155 |
No log | 91.0 | 364 | 0.8201 |
No log | 92.0 | 368 | 0.8253 |
No log | 93.0 | 372 | 0.8252 |
No log | 94.0 | 376 | 0.8227 |
No log | 95.0 | 380 | 0.8195 |
No log | 96.0 | 384 | 0.8156 |
No log | 97.0 | 388 | 0.8132 |
No log | 98.0 | 392 | 0.8125 |
No log | 99.0 | 396 | 0.8117 |
No log | 100.0 | 400 | 0.8115 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.7
- Tokenizers 0.15.0
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