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| 1 |
+
---
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| 2 |
+
library_name: transformers
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| 3 |
+
license: mit
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| 4 |
+
base_model: microsoft/deberta-v3-base
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| 5 |
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tags:
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| 6 |
+
- generated_from_trainer
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| 7 |
+
metrics:
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| 8 |
+
- accuracy
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| 9 |
+
- precision
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| 10 |
+
- recall
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| 11 |
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- f1
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| 12 |
+
model-index:
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| 13 |
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- name: judge_answer___35_deberta_large_enwiki-answerability-2411
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| 14 |
+
results: []
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| 15 |
+
---
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| 16 |
+
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| 17 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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| 18 |
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should probably proofread and complete it, then remove this comment. -->
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| 19 |
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| 20 |
+
# judge_answer___35_deberta_large_enwiki-answerability-2411
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| 21 |
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| 22 |
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This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset.
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| 23 |
+
It achieves the following results on the evaluation set:
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| 24 |
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- Loss: 0.2672
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| 25 |
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- Accuracy: 0.9451
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| 26 |
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- Precision: 0.9448
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| 27 |
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- Recall: 0.9448
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| 28 |
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- F1: 0.9448
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| 29 |
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- F0.5: 0.9448
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| 30 |
+
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| 31 |
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## Model description
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| 32 |
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| 33 |
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More information needed
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| 34 |
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| 35 |
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## Intended uses & limitations
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| 36 |
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| 37 |
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More information needed
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| 38 |
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| 39 |
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## Training and evaluation data
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| 40 |
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| 41 |
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More information needed
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| 42 |
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| 43 |
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## Training procedure
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| 44 |
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| 45 |
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### Training hyperparameters
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| 46 |
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| 47 |
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The following hyperparameters were used during training:
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| 48 |
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- learning_rate: 1e-05
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| 49 |
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- train_batch_size: 8
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| 50 |
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- eval_batch_size: 8
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| 51 |
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- seed: 42
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| 52 |
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- gradient_accumulation_steps: 2
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| 53 |
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- total_train_batch_size: 16
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| 54 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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| 55 |
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- lr_scheduler_type: linear
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| 56 |
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- lr_scheduler_warmup_steps: 500
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| 57 |
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- num_epochs: 4
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| 58 |
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- mixed_precision_training: Native AMP
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| 59 |
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| 60 |
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### Training results
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| 61 |
+
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| 62 |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | F0.5 |
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| 63 |
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|:-------------:|:------:|:------:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
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| 64 |
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| 0.2671 | 0.0340 | 1000 | 0.2442 | 0.9172 | 0.9081 | 0.9273 | 0.9176 | 0.9119 |
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| 65 |
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| 0.2188 | 0.0680 | 2000 | 0.2383 | 0.9241 | 0.9114 | 0.9387 | 0.9248 | 0.9167 |
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| 66 |
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| 0.2204 | 0.1020 | 3000 | 0.2081 | 0.9287 | 0.9449 | 0.9098 | 0.9270 | 0.9376 |
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| 67 |
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| 0.2101 | 0.1360 | 4000 | 0.2258 | 0.93 | 0.9294 | 0.9299 | 0.9297 | 0.9295 |
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| 68 |
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| 0.2087 | 0.1700 | 5000 | 0.2156 | 0.9238 | 0.9566 | 0.8871 | 0.9206 | 0.9419 |
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| 69 |
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| 0.2006 | 0.2040 | 6000 | 0.2123 | 0.9331 | 0.9307 | 0.9351 | 0.9329 | 0.9316 |
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| 70 |
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| 0.1973 | 0.2380 | 7000 | 0.1832 | 0.9387 | 0.9377 | 0.9392 | 0.9384 | 0.9380 |
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| 71 |
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| 0.2055 | 0.2720 | 8000 | 0.2003 | 0.9338 | 0.9399 | 0.9263 | 0.9330 | 0.9371 |
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| 72 |
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| 0.2002 | 0.3060 | 9000 | 0.2280 | 0.9351 | 0.9271 | 0.9438 | 0.9354 | 0.9304 |
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| 73 |
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| 0.1927 | 0.3400 | 10000 | 0.2304 | 0.9333 | 0.9106 | 0.9603 | 0.9348 | 0.9201 |
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| 74 |
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| 0.2001 | 0.3740 | 11000 | 0.1964 | 0.9349 | 0.9395 | 0.9289 | 0.9342 | 0.9374 |
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| 75 |
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| 0.1918 | 0.4080 | 12000 | 0.1843 | 0.9356 | 0.9364 | 0.9340 | 0.9352 | 0.9360 |
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| 76 |
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| 0.1913 | 0.4420 | 13000 | 0.2252 | 0.9321 | 0.9609 | 0.9 | 0.9295 | 0.9481 |
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| 77 |
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| 0.1852 | 0.4760 | 14000 | 0.1806 | 0.9362 | 0.9272 | 0.9459 | 0.9365 | 0.9309 |
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| 78 |
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| 0.1796 | 0.5100 | 15000 | 0.2018 | 0.9423 | 0.9482 | 0.9351 | 0.9416 | 0.9456 |
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| 79 |
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| 0.1862 | 0.5441 | 16000 | 0.2066 | 0.9344 | 0.9446 | 0.9222 | 0.9332 | 0.9400 |
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| 80 |
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| 0.1942 | 0.5781 | 17000 | 0.2123 | 0.9367 | 0.9189 | 0.9572 | 0.9376 | 0.9263 |
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| 81 |
+
| 0.1864 | 0.6121 | 18000 | 0.1822 | 0.9377 | 0.9564 | 0.9165 | 0.9360 | 0.9482 |
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| 82 |
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| 0.1939 | 0.6461 | 19000 | 0.2125 | 0.9359 | 0.9447 | 0.9253 | 0.9349 | 0.9408 |
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| 83 |
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| 0.185 | 0.6801 | 20000 | 0.2039 | 0.9364 | 0.9312 | 0.9418 | 0.9364 | 0.9333 |
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| 84 |
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| 0.1844 | 0.7141 | 21000 | 0.1742 | 0.9392 | 0.9396 | 0.9381 | 0.9389 | 0.9393 |
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| 85 |
+
| 0.1818 | 0.7481 | 22000 | 0.1892 | 0.9405 | 0.9407 | 0.9397 | 0.9402 | 0.9405 |
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| 86 |
+
| 0.1828 | 0.7821 | 23000 | 0.2015 | 0.9379 | 0.9502 | 0.9237 | 0.9367 | 0.9447 |
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| 87 |
+
| 0.1771 | 0.8161 | 24000 | 0.1985 | 0.94 | 0.9452 | 0.9335 | 0.9393 | 0.9428 |
|
| 88 |
+
| 0.1772 | 0.8501 | 25000 | 0.1672 | 0.9426 | 0.9540 | 0.9294 | 0.9415 | 0.9489 |
|
| 89 |
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| 0.1859 | 0.8841 | 26000 | 0.1748 | 0.9362 | 0.9126 | 0.9639 | 0.9376 | 0.9225 |
|
| 90 |
+
| 0.189 | 0.9181 | 27000 | 0.1642 | 0.9464 | 0.9427 | 0.95 | 0.9463 | 0.9442 |
|
| 91 |
+
| 0.1774 | 0.9521 | 28000 | 0.1767 | 0.9462 | 0.9369 | 0.9562 | 0.9464 | 0.9407 |
|
| 92 |
+
| 0.1658 | 0.9861 | 29000 | 0.1958 | 0.9431 | 0.9343 | 0.9526 | 0.9433 | 0.9379 |
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| 93 |
+
| 0.1574 | 1.0201 | 30000 | 0.2119 | 0.9428 | 0.9329 | 0.9536 | 0.9432 | 0.9370 |
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| 94 |
+
| 0.1588 | 1.0541 | 31000 | 0.1801 | 0.9408 | 0.9548 | 0.9247 | 0.9395 | 0.9486 |
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| 95 |
+
| 0.1578 | 1.0881 | 32000 | 0.2292 | 0.9418 | 0.9525 | 0.9294 | 0.9408 | 0.9478 |
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| 96 |
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| 0.1597 | 1.1221 | 33000 | 0.1971 | 0.9415 | 0.9417 | 0.9407 | 0.9412 | 0.9415 |
|
| 97 |
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| 0.155 | 1.1561 | 34000 | 0.2235 | 0.9426 | 0.9409 | 0.9438 | 0.9424 | 0.9415 |
|
| 98 |
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| 0.1594 | 1.1901 | 35000 | 0.1763 | 0.9449 | 0.9425 | 0.9469 | 0.9447 | 0.9434 |
|
| 99 |
+
| 0.1655 | 1.2241 | 36000 | 0.1773 | 0.9444 | 0.9420 | 0.9464 | 0.9442 | 0.9429 |
|
| 100 |
+
| 0.1682 | 1.2581 | 37000 | 0.2021 | 0.94 | 0.9383 | 0.9412 | 0.9398 | 0.9389 |
|
| 101 |
+
| 0.1495 | 1.2921 | 38000 | 0.1954 | 0.9421 | 0.9364 | 0.9479 | 0.9421 | 0.9386 |
|
| 102 |
+
| 0.1567 | 1.3261 | 39000 | 0.2083 | 0.9451 | 0.9481 | 0.9412 | 0.9446 | 0.9467 |
|
| 103 |
+
| 0.1687 | 1.3601 | 40000 | 0.1800 | 0.9415 | 0.9573 | 0.9237 | 0.9402 | 0.9504 |
|
| 104 |
+
| 0.1599 | 1.3941 | 41000 | 0.1816 | 0.9444 | 0.9580 | 0.9289 | 0.9432 | 0.9520 |
|
| 105 |
+
| 0.1655 | 1.4281 | 42000 | 0.1852 | 0.9472 | 0.9423 | 0.9521 | 0.9472 | 0.9443 |
|
| 106 |
+
| 0.1579 | 1.4621 | 43000 | 0.1888 | 0.9446 | 0.9452 | 0.9433 | 0.9443 | 0.9449 |
|
| 107 |
+
| 0.1606 | 1.4961 | 44000 | 0.1880 | 0.9456 | 0.9381 | 0.9536 | 0.9458 | 0.9412 |
|
| 108 |
+
| 0.1522 | 1.5301 | 45000 | 0.2139 | 0.9464 | 0.9464 | 0.9459 | 0.9461 | 0.9463 |
|
| 109 |
+
| 0.1497 | 1.5641 | 46000 | 0.1971 | 0.9436 | 0.9470 | 0.9392 | 0.9431 | 0.9454 |
|
| 110 |
+
| 0.159 | 1.5982 | 47000 | 0.1935 | 0.9418 | 0.9192 | 0.9680 | 0.9430 | 0.9286 |
|
| 111 |
+
| 0.1582 | 1.6322 | 48000 | 0.1841 | 0.9441 | 0.9344 | 0.9546 | 0.9444 | 0.9384 |
|
| 112 |
+
| 0.1505 | 1.6662 | 49000 | 0.2033 | 0.9405 | 0.9322 | 0.9495 | 0.9408 | 0.9356 |
|
| 113 |
+
| 0.1503 | 1.7002 | 50000 | 0.1974 | 0.9454 | 0.9377 | 0.9536 | 0.9456 | 0.9408 |
|
| 114 |
+
| 0.1651 | 1.7342 | 51000 | 0.1995 | 0.9438 | 0.9335 | 0.9552 | 0.9442 | 0.9378 |
|
| 115 |
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| 0.1544 | 1.7682 | 52000 | 0.1831 | 0.9462 | 0.9325 | 0.9613 | 0.9467 | 0.9381 |
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| 116 |
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| 0.1618 | 1.8022 | 53000 | 0.2018 | 0.9413 | 0.9577 | 0.9227 | 0.9399 | 0.9505 |
|
| 117 |
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| 0.1585 | 1.8362 | 54000 | 0.1897 | 0.9456 | 0.9342 | 0.9582 | 0.9461 | 0.9389 |
|
| 118 |
+
| 0.1604 | 1.8702 | 55000 | 0.1774 | 0.9472 | 0.9478 | 0.9459 | 0.9469 | 0.9474 |
|
| 119 |
+
| 0.1598 | 1.9042 | 56000 | 0.1740 | 0.9451 | 0.9556 | 0.9330 | 0.9442 | 0.9510 |
|
| 120 |
+
| 0.1522 | 1.9382 | 57000 | 0.2008 | 0.9449 | 0.9499 | 0.9387 | 0.9443 | 0.9476 |
|
| 121 |
+
| 0.1477 | 1.9722 | 58000 | 0.1893 | 0.9449 | 0.9389 | 0.9510 | 0.9449 | 0.9413 |
|
| 122 |
+
| 0.1414 | 2.0062 | 59000 | 0.2214 | 0.9459 | 0.9454 | 0.9459 | 0.9456 | 0.9455 |
|
| 123 |
+
| 0.1263 | 2.0402 | 60000 | 0.2393 | 0.9464 | 0.9543 | 0.9371 | 0.9456 | 0.9508 |
|
| 124 |
+
| 0.1281 | 2.0742 | 61000 | 0.2349 | 0.9479 | 0.9461 | 0.9495 | 0.9478 | 0.9468 |
|
| 125 |
+
| 0.1368 | 2.1082 | 62000 | 0.2080 | 0.9449 | 0.9444 | 0.9448 | 0.9446 | 0.9445 |
|
| 126 |
+
| 0.1299 | 2.1422 | 63000 | 0.2494 | 0.9421 | 0.9478 | 0.9351 | 0.9414 | 0.9452 |
|
| 127 |
+
| 0.1315 | 2.1762 | 64000 | 0.2268 | 0.9464 | 0.9515 | 0.9402 | 0.9458 | 0.9492 |
|
| 128 |
+
| 0.1385 | 2.2102 | 65000 | 0.2346 | 0.9464 | 0.9510 | 0.9407 | 0.9458 | 0.9489 |
|
| 129 |
+
| 0.1314 | 2.2442 | 66000 | 0.2218 | 0.9428 | 0.9564 | 0.9273 | 0.9416 | 0.9504 |
|
| 130 |
+
| 0.1404 | 2.2782 | 67000 | 0.2182 | 0.9454 | 0.9368 | 0.9546 | 0.9456 | 0.9403 |
|
| 131 |
+
| 0.1388 | 2.3122 | 68000 | 0.2175 | 0.9469 | 0.9370 | 0.9577 | 0.9472 | 0.9410 |
|
| 132 |
+
| 0.1318 | 2.3462 | 69000 | 0.2439 | 0.9423 | 0.9530 | 0.9299 | 0.9413 | 0.9483 |
|
| 133 |
+
| 0.1302 | 2.3802 | 70000 | 0.2290 | 0.9456 | 0.9472 | 0.9433 | 0.9452 | 0.9464 |
|
| 134 |
+
| 0.1249 | 2.4142 | 71000 | 0.2438 | 0.9433 | 0.9470 | 0.9387 | 0.9428 | 0.9453 |
|
| 135 |
+
| 0.1424 | 2.4482 | 72000 | 0.2356 | 0.9423 | 0.9273 | 0.9593 | 0.9430 | 0.9335 |
|
| 136 |
+
| 0.1378 | 2.4822 | 73000 | 0.2081 | 0.9467 | 0.9473 | 0.9454 | 0.9463 | 0.9469 |
|
| 137 |
+
| 0.1305 | 2.5162 | 74000 | 0.2488 | 0.9446 | 0.9504 | 0.9376 | 0.9440 | 0.9478 |
|
| 138 |
+
| 0.1257 | 2.5502 | 75000 | 0.2489 | 0.9454 | 0.9472 | 0.9428 | 0.9450 | 0.9463 |
|
| 139 |
+
| 0.1249 | 2.5842 | 76000 | 0.2599 | 0.9428 | 0.9623 | 0.9211 | 0.9413 | 0.9538 |
|
| 140 |
+
| 0.1314 | 2.6182 | 77000 | 0.2259 | 0.9472 | 0.9520 | 0.9412 | 0.9466 | 0.9499 |
|
| 141 |
+
| 0.1301 | 2.6522 | 78000 | 0.2352 | 0.9472 | 0.9464 | 0.9474 | 0.9469 | 0.9466 |
|
| 142 |
+
| 0.1287 | 2.6863 | 79000 | 0.2348 | 0.9436 | 0.9484 | 0.9376 | 0.9430 | 0.9462 |
|
| 143 |
+
| 0.1252 | 2.7203 | 80000 | 0.2225 | 0.9462 | 0.9454 | 0.9464 | 0.9459 | 0.9456 |
|
| 144 |
+
| 0.1258 | 2.7543 | 81000 | 0.2302 | 0.9454 | 0.9399 | 0.9510 | 0.9454 | 0.9421 |
|
| 145 |
+
| 0.1345 | 2.7883 | 82000 | 0.2191 | 0.9479 | 0.9479 | 0.9474 | 0.9477 | 0.9478 |
|
| 146 |
+
| 0.1344 | 2.8223 | 83000 | 0.2374 | 0.9459 | 0.9552 | 0.9351 | 0.9450 | 0.9511 |
|
| 147 |
+
| 0.1219 | 2.8563 | 84000 | 0.2361 | 0.9454 | 0.9542 | 0.9351 | 0.9445 | 0.9503 |
|
| 148 |
+
| 0.1346 | 2.8903 | 85000 | 0.2135 | 0.9472 | 0.9568 | 0.9361 | 0.9463 | 0.9526 |
|
| 149 |
+
| 0.1323 | 2.9243 | 86000 | 0.2245 | 0.9449 | 0.9561 | 0.9320 | 0.9439 | 0.9512 |
|
| 150 |
+
| 0.1341 | 2.9583 | 87000 | 0.2200 | 0.9444 | 0.9518 | 0.9356 | 0.9436 | 0.9485 |
|
| 151 |
+
| 0.1257 | 2.9923 | 88000 | 0.2280 | 0.9492 | 0.9508 | 0.9469 | 0.9489 | 0.9500 |
|
| 152 |
+
| 0.1126 | 3.0263 | 89000 | 0.2499 | 0.9469 | 0.9525 | 0.9402 | 0.9463 | 0.95 |
|
| 153 |
+
| 0.0964 | 3.0603 | 90000 | 0.2556 | 0.9467 | 0.9520 | 0.9402 | 0.9461 | 0.9496 |
|
| 154 |
+
| 0.1104 | 3.0943 | 91000 | 0.2575 | 0.9451 | 0.9533 | 0.9356 | 0.9443 | 0.9497 |
|
| 155 |
+
| 0.105 | 3.1283 | 92000 | 0.2610 | 0.9469 | 0.9520 | 0.9407 | 0.9463 | 0.9497 |
|
| 156 |
+
| 0.1098 | 3.1623 | 93000 | 0.2514 | 0.9459 | 0.9431 | 0.9485 | 0.9458 | 0.9442 |
|
| 157 |
+
| 0.0875 | 3.1963 | 94000 | 0.2900 | 0.9441 | 0.9489 | 0.9381 | 0.9435 | 0.9467 |
|
| 158 |
+
| 0.103 | 3.2303 | 95000 | 0.2538 | 0.9487 | 0.9536 | 0.9428 | 0.9482 | 0.9514 |
|
| 159 |
+
| 0.1037 | 3.2643 | 96000 | 0.2641 | 0.9436 | 0.9428 | 0.9438 | 0.9433 | 0.9430 |
|
| 160 |
+
| 0.1132 | 3.2983 | 97000 | 0.2516 | 0.9433 | 0.9456 | 0.9402 | 0.9429 | 0.9445 |
|
| 161 |
+
| 0.1034 | 3.3323 | 98000 | 0.2816 | 0.9433 | 0.9451 | 0.9407 | 0.9429 | 0.9442 |
|
| 162 |
+
| 0.1157 | 3.3663 | 99000 | 0.2556 | 0.9467 | 0.9510 | 0.9412 | 0.9461 | 0.9491 |
|
| 163 |
+
| 0.1086 | 3.4003 | 100000 | 0.2515 | 0.9469 | 0.9506 | 0.9423 | 0.9464 | 0.9489 |
|
| 164 |
+
| 0.1002 | 3.4343 | 101000 | 0.2601 | 0.9459 | 0.9463 | 0.9448 | 0.9456 | 0.9460 |
|
| 165 |
+
| 0.1065 | 3.4683 | 102000 | 0.2547 | 0.9464 | 0.9491 | 0.9428 | 0.9460 | 0.9479 |
|
| 166 |
+
| 0.1048 | 3.5023 | 103000 | 0.2578 | 0.9462 | 0.9510 | 0.9402 | 0.9456 | 0.9488 |
|
| 167 |
+
| 0.097 | 3.5363 | 104000 | 0.2672 | 0.9474 | 0.9497 | 0.9443 | 0.9470 | 0.9486 |
|
| 168 |
+
| 0.1078 | 3.5703 | 105000 | 0.2575 | 0.9449 | 0.9495 | 0.9392 | 0.9443 | 0.9474 |
|
| 169 |
+
| 0.1043 | 3.6043 | 106000 | 0.2617 | 0.9462 | 0.9440 | 0.9479 | 0.9460 | 0.9448 |
|
| 170 |
+
| 0.0972 | 3.6383 | 107000 | 0.2604 | 0.9449 | 0.9462 | 0.9428 | 0.9445 | 0.9455 |
|
| 171 |
+
| 0.0907 | 3.6723 | 108000 | 0.2635 | 0.9456 | 0.9481 | 0.9423 | 0.9452 | 0.9470 |
|
| 172 |
+
| 0.1044 | 3.7063 | 109000 | 0.2697 | 0.9449 | 0.9476 | 0.9412 | 0.9444 | 0.9463 |
|
| 173 |
+
| 0.1106 | 3.7404 | 110000 | 0.2588 | 0.9459 | 0.9500 | 0.9407 | 0.9454 | 0.9482 |
|
| 174 |
+
| 0.1021 | 3.7744 | 111000 | 0.2723 | 0.9449 | 0.9495 | 0.9392 | 0.9443 | 0.9474 |
|
| 175 |
+
| 0.0958 | 3.8084 | 112000 | 0.2674 | 0.9449 | 0.9439 | 0.9454 | 0.9446 | 0.9442 |
|
| 176 |
+
| 0.1042 | 3.8424 | 113000 | 0.2661 | 0.9446 | 0.9430 | 0.9459 | 0.9444 | 0.9435 |
|
| 177 |
+
| 0.0943 | 3.8764 | 114000 | 0.2673 | 0.9454 | 0.9467 | 0.9433 | 0.9450 | 0.9460 |
|
| 178 |
+
| 0.094 | 3.9104 | 115000 | 0.2670 | 0.9462 | 0.9473 | 0.9443 | 0.9458 | 0.9467 |
|
| 179 |
+
| 0.1024 | 3.9444 | 116000 | 0.2683 | 0.9459 | 0.9458 | 0.9454 | 0.9456 | 0.9458 |
|
| 180 |
+
| 0.0957 | 3.9784 | 117000 | 0.2672 | 0.9451 | 0.9448 | 0.9448 | 0.9448 | 0.9448 |
|
| 181 |
+
|
| 182 |
+
|
| 183 |
+
### Framework versions
|
| 184 |
+
|
| 185 |
+
- Transformers 4.46.2
|
| 186 |
+
- Pytorch 2.4.1+cu124
|
| 187 |
+
- Datasets 3.1.0
|
| 188 |
+
- Tokenizers 0.20.3
|
model.safetensors
CHANGED
|
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|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
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|
| 3 |
size 737719272
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
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| 3 |
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|