StatementOfWork_Generator_Omega_BS_512_2
This model is a fine-tuned version of distilgpt2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8120
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: 50
- eval_batch_size: 50
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 150
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 4 | 0.9839 |
| No log | 2.0 | 8 | 0.9786 |
| No log | 3.0 | 12 | 0.9767 |
| No log | 4.0 | 16 | 0.9757 |
| No log | 5.0 | 20 | 0.9716 |
| No log | 6.0 | 24 | 0.9670 |
| No log | 7.0 | 28 | 0.9663 |
| No log | 8.0 | 32 | 0.9627 |
| No log | 9.0 | 36 | 0.9571 |
| No log | 10.0 | 40 | 0.9573 |
| No log | 11.0 | 44 | 0.9520 |
| No log | 12.0 | 48 | 0.9511 |
| No log | 13.0 | 52 | 0.9486 |
| No log | 14.0 | 56 | 0.9425 |
| No log | 15.0 | 60 | 0.9440 |
| No log | 16.0 | 64 | 0.9392 |
| No log | 17.0 | 68 | 0.9357 |
| No log | 18.0 | 72 | 0.9368 |
| No log | 19.0 | 76 | 0.9333 |
| No log | 20.0 | 80 | 0.9284 |
| No log | 21.0 | 84 | 0.9260 |
| No log | 22.0 | 88 | 0.9244 |
| No log | 23.0 | 92 | 0.9228 |
| No log | 24.0 | 96 | 0.9192 |
| No log | 25.0 | 100 | 0.9163 |
| No log | 26.0 | 104 | 0.9164 |
| No log | 27.0 | 108 | 0.9135 |
| No log | 28.0 | 112 | 0.9107 |
| No log | 29.0 | 116 | 0.9105 |
| No log | 30.0 | 120 | 0.9068 |
| No log | 31.0 | 124 | 0.9050 |
| No log | 32.0 | 128 | 0.9034 |
| No log | 33.0 | 132 | 0.9012 |
| No log | 34.0 | 136 | 0.8966 |
| No log | 35.0 | 140 | 0.8968 |
| No log | 36.0 | 144 | 0.8953 |
| No log | 37.0 | 148 | 0.8920 |
| No log | 38.0 | 152 | 0.8920 |
| No log | 39.0 | 156 | 0.8912 |
| No log | 40.0 | 160 | 0.8877 |
| No log | 41.0 | 164 | 0.8871 |
| No log | 42.0 | 168 | 0.8857 |
| No log | 43.0 | 172 | 0.8800 |
| No log | 44.0 | 176 | 0.8789 |
| No log | 45.0 | 180 | 0.8831 |
| No log | 46.0 | 184 | 0.8794 |
| No log | 47.0 | 188 | 0.8757 |
| No log | 48.0 | 192 | 0.8760 |
| No log | 49.0 | 196 | 0.8730 |
| No log | 50.0 | 200 | 0.8726 |
| No log | 51.0 | 204 | 0.8719 |
| No log | 52.0 | 208 | 0.8689 |
| No log | 53.0 | 212 | 0.8691 |
| No log | 54.0 | 216 | 0.8679 |
| No log | 55.0 | 220 | 0.8633 |
| No log | 56.0 | 224 | 0.8623 |
| No log | 57.0 | 228 | 0.8624 |
| No log | 58.0 | 232 | 0.8610 |
| No log | 59.0 | 236 | 0.8601 |
| No log | 60.0 | 240 | 0.8586 |
| No log | 61.0 | 244 | 0.8583 |
| No log | 62.0 | 248 | 0.8564 |
| No log | 63.0 | 252 | 0.8552 |
| No log | 64.0 | 256 | 0.8545 |
| No log | 65.0 | 260 | 0.8526 |
| No log | 66.0 | 264 | 0.8513 |
| No log | 67.0 | 268 | 0.8508 |
| No log | 68.0 | 272 | 0.8501 |
| No log | 69.0 | 276 | 0.8484 |
| No log | 70.0 | 280 | 0.8479 |
| No log | 71.0 | 284 | 0.8465 |
| No log | 72.0 | 288 | 0.8464 |
| No log | 73.0 | 292 | 0.8452 |
| No log | 74.0 | 296 | 0.8442 |
| No log | 75.0 | 300 | 0.8443 |
| No log | 76.0 | 304 | 0.8425 |
| No log | 77.0 | 308 | 0.8410 |
| No log | 78.0 | 312 | 0.8402 |
| No log | 79.0 | 316 | 0.8394 |
| No log | 80.0 | 320 | 0.8385 |
| No log | 81.0 | 324 | 0.8380 |
| No log | 82.0 | 328 | 0.8380 |
| No log | 83.0 | 332 | 0.8369 |
| No log | 84.0 | 336 | 0.8356 |
| No log | 85.0 | 340 | 0.8351 |
| No log | 86.0 | 344 | 0.8343 |
| No log | 87.0 | 348 | 0.8326 |
| No log | 88.0 | 352 | 0.8331 |
| No log | 89.0 | 356 | 0.8328 |
| No log | 90.0 | 360 | 0.8306 |
| No log | 91.0 | 364 | 0.8310 |
| No log | 92.0 | 368 | 0.8314 |
| No log | 93.0 | 372 | 0.8295 |
| No log | 94.0 | 376 | 0.8287 |
| No log | 95.0 | 380 | 0.8286 |
| No log | 96.0 | 384 | 0.8276 |
| No log | 97.0 | 388 | 0.8270 |
| No log | 98.0 | 392 | 0.8262 |
| No log | 99.0 | 396 | 0.8251 |
| No log | 100.0 | 400 | 0.8241 |
| No log | 101.0 | 404 | 0.8231 |
| No log | 102.0 | 408 | 0.8225 |
| No log | 103.0 | 412 | 0.8235 |
| No log | 104.0 | 416 | 0.8234 |
| No log | 105.0 | 420 | 0.8225 |
| No log | 106.0 | 424 | 0.8219 |
| No log | 107.0 | 428 | 0.8209 |
| No log | 108.0 | 432 | 0.8204 |
| No log | 109.0 | 436 | 0.8195 |
| No log | 110.0 | 440 | 0.8191 |
| No log | 111.0 | 444 | 0.8191 |
| No log | 112.0 | 448 | 0.8193 |
| No log | 113.0 | 452 | 0.8197 |
| No log | 114.0 | 456 | 0.8191 |
| No log | 115.0 | 460 | 0.8179 |
| No log | 116.0 | 464 | 0.8176 |
| No log | 117.0 | 468 | 0.8173 |
| No log | 118.0 | 472 | 0.8172 |
| No log | 119.0 | 476 | 0.8174 |
| No log | 120.0 | 480 | 0.8171 |
| No log | 121.0 | 484 | 0.8169 |
| No log | 122.0 | 488 | 0.8168 |
| No log | 123.0 | 492 | 0.8162 |
| No log | 124.0 | 496 | 0.8161 |
| 0.3706 | 125.0 | 500 | 0.8160 |
| 0.3706 | 126.0 | 504 | 0.8156 |
| 0.3706 | 127.0 | 508 | 0.8145 |
| 0.3706 | 128.0 | 512 | 0.8143 |
| 0.3706 | 129.0 | 516 | 0.8143 |
| 0.3706 | 130.0 | 520 | 0.8145 |
| 0.3706 | 131.0 | 524 | 0.8147 |
| 0.3706 | 132.0 | 528 | 0.8142 |
| 0.3706 | 133.0 | 532 | 0.8136 |
| 0.3706 | 134.0 | 536 | 0.8136 |
| 0.3706 | 135.0 | 540 | 0.8138 |
| 0.3706 | 136.0 | 544 | 0.8139 |
| 0.3706 | 137.0 | 548 | 0.8140 |
| 0.3706 | 138.0 | 552 | 0.8138 |
| 0.3706 | 139.0 | 556 | 0.8134 |
| 0.3706 | 140.0 | 560 | 0.8130 |
| 0.3706 | 141.0 | 564 | 0.8128 |
| 0.3706 | 142.0 | 568 | 0.8127 |
| 0.3706 | 143.0 | 572 | 0.8126 |
| 0.3706 | 144.0 | 576 | 0.8124 |
| 0.3706 | 145.0 | 580 | 0.8123 |
| 0.3706 | 146.0 | 584 | 0.8121 |
| 0.3706 | 147.0 | 588 | 0.8120 |
| 0.3706 | 148.0 | 592 | 0.8120 |
| 0.3706 | 149.0 | 596 | 0.8120 |
| 0.3706 | 150.0 | 600 | 0.8120 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Base model
distilbert/distilgpt2