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adbaral
/
langcache-reranker-v1-wdwr

Text Ranking
sentence-transformers
Safetensors
English
modernbert
cross-encoder
text-classification
sentence-pair-classification
semantic-similarity
semantic-search
retrieval
reranking
Generated from Trainer
dataset_size:1047690
loss:BinaryCrossEntropyLoss
Eval Results
Model card Files
xet
Community
Aditeya Baral commited on
Commit
1aad08e
·
verified ·
1 Parent(s): b25c098

Add new CrossEncoder model

Browse files
Files changed (2) hide show
  1. README.md +123 -123
  2. model.safetensors +1 -1
README.md CHANGED
@@ -38,25 +38,25 @@ model-index:
38
  type: val
39
  metrics:
40
  - type: accuracy
41
- value: 0.7787031528851874
42
  name: Accuracy
43
  - type: accuracy_threshold
44
- value: 0.6814298629760742
45
  name: Accuracy Threshold
46
  - type: f1
47
- value: 0.6997420725231376
48
  name: F1
49
  - type: f1_threshold
50
- value: 0.0551694892346859
51
  name: F1 Threshold
52
  - type: precision
53
- value: 0.6770405167351732
54
  name: Precision
55
  - type: recall
56
- value: 0.7240188383045526
57
  name: Recall
58
  - type: average_precision
59
- value: 0.7859297230871715
60
  name: Average Precision
61
  - task:
62
  type: cross-encoder-classification
@@ -188,13 +188,13 @@ You can finetune this model on your own dataset.
188
 
189
  | Metric | val | test |
190
  |:----------------------|:-----------|:-----------|
191
- | accuracy | 0.7787 | 0.723 |
192
- | accuracy_threshold | 0.6814 | 0.9352 |
193
- | f1 | 0.6997 | 0.7144 |
194
- | f1_threshold | 0.0552 | 0.9143 |
195
- | precision | 0.677 | 0.6303 |
196
- | recall | 0.724 | 0.8245 |
197
- | **average_precision** | **0.7859** | **0.6907** |
198
 
199
  <!--
200
  ## Bias, Risks and Limitations
@@ -325,7 +325,7 @@ You can finetune this model on your own dataset.
325
  - `bf16_full_eval`: False
326
  - `fp16_full_eval`: False
327
  - `tf32`: None
328
- - `local_rank`: 2
329
  - `ddp_backend`: None
330
  - `tpu_num_cores`: None
331
  - `tpu_metrics_debug`: False
@@ -406,115 +406,115 @@ You can finetune this model on your own dataset.
406
  | Epoch | Step | Training Loss | Validation Loss | val_average_precision | test_average_precision |
407
  |:----------:|:--------:|:-------------:|:---------------:|:---------------------:|:----------------------:|
408
  | -1 | -1 | - | - | 0.7676 | 0.6907 |
409
- | 0.1833 | 1000 | 0.3563 | 0.4805 | 0.7659 | - |
410
- | 0.3666 | 2000 | 0.2065 | 0.5394 | 0.8041 | - |
411
- | 0.5499 | 3000 | 0.1983 | 0.5019 | 0.8177 | - |
412
- | **0.7331** | **4000** | **0.1923** | **0.5109** | **0.8233** | **-** |
413
- | 0.9164 | 5000 | 0.1886 | 0.4726 | 0.8190 | - |
414
- | 1.0997 | 6000 | 0.183 | 0.5062 | 0.7742 | - |
415
- | 1.2830 | 7000 | 0.1838 | 0.5152 | 0.8032 | - |
416
- | 1.4663 | 8000 | 0.1858 | 0.5105 | 0.8073 | - |
417
- | 1.6496 | 9000 | 0.1905 | 0.5052 | 0.7905 | - |
418
- | 1.8328 | 10000 | 0.1926 | 0.5316 | 0.7734 | - |
419
- | 2.0161 | 11000 | 0.1951 | 0.5340 | 0.7808 | - |
420
- | 2.1994 | 12000 | 0.1853 | 0.5573 | 0.7361 | - |
421
- | 2.3827 | 13000 | 0.1848 | 0.5530 | 0.7769 | - |
422
- | 2.5660 | 14000 | 0.1813 | 0.5754 | 0.7645 | - |
423
- | 2.7493 | 15000 | 0.1793 | 0.5316 | 0.7719 | - |
424
- | 2.9326 | 16000 | 0.1778 | 0.5230 | 0.7864 | - |
425
- | 3.1158 | 17000 | 0.1681 | 0.5246 | 0.7852 | - |
426
- | 3.2991 | 18000 | 0.1662 | 0.4946 | 0.7914 | - |
427
- | 3.4824 | 19000 | 0.1648 | 0.5262 | 0.7864 | - |
428
- | 3.6657 | 20000 | 0.1649 | 0.5007 | 0.7950 | - |
429
- | 3.8490 | 21000 | 0.1633 | 0.5368 | 0.7907 | - |
430
- | 4.0323 | 22000 | 0.1602 | 0.5559 | 0.7802 | - |
431
- | 4.2155 | 23000 | 0.149 | 0.5796 | 0.7884 | - |
432
- | 4.3988 | 24000 | 0.1486 | 0.5322 | 0.7870 | - |
433
- | 4.5821 | 25000 | 0.1495 | 0.5142 | 0.7875 | - |
434
  | 4.7654 | 26000 | 0.1493 | 0.5203 | 0.7866 | - |
435
- | 4.9487 | 27000 | 0.1498 | 0.5433 | 0.7750 | - |
436
- | 5.1320 | 28000 | 0.1391 | 0.5589 | 0.7663 | - |
437
- | 5.3152 | 29000 | 0.1346 | 0.5267 | 0.7769 | - |
438
- | 5.4985 | 30000 | 0.1367 | 0.5657 | 0.7791 | - |
439
- | 5.6818 | 31000 | 0.1358 | 0.5631 | 0.7868 | - |
440
- | 5.8651 | 32000 | 0.136 | 0.5444 | 0.7884 | - |
441
- | 6.0484 | 33000 | 0.1346 | 0.5605 | 0.7816 | - |
442
- | 6.2317 | 34000 | 0.1222 | 0.5399 | 0.7857 | - |
443
- | 6.4150 | 35000 | 0.1241 | 0.5272 | 0.7840 | - |
444
- | 6.5982 | 36000 | 0.1243 | 0.6096 | 0.7836 | - |
445
- | 6.7815 | 37000 | 0.1266 | 0.5661 | 0.7847 | - |
446
- | 6.9648 | 38000 | 0.1246 | 0.5341 | 0.7940 | - |
447
- | 7.1481 | 39000 | 0.1128 | 0.6223 | 0.7875 | - |
448
- | 7.3314 | 40000 | 0.1124 | 0.5485 | 0.7712 | - |
449
- | 7.5147 | 41000 | 0.1127 | 0.5375 | 0.7898 | - |
450
- | 7.6979 | 42000 | 0.1122 | 0.5231 | 0.7945 | - |
451
- | 7.8812 | 43000 | 0.1141 | 0.5608 | 0.7886 | - |
452
- | 8.0645 | 44000 | 0.1088 | 0.6511 | 0.7848 | - |
453
- | 8.2478 | 45000 | 0.0998 | 0.6217 | 0.7799 | - |
454
- | 8.4311 | 46000 | 0.1017 | 0.6000 | 0.7847 | - |
455
- | 8.6144 | 47000 | 0.1031 | 0.5469 | 0.7829 | - |
456
- | 8.7977 | 48000 | 0.1012 | 0.5862 | 0.7792 | - |
457
- | 8.9809 | 49000 | 0.1031 | 0.5527 | 0.7849 | - |
458
- | 9.1642 | 50000 | 0.0921 | 0.5460 | 0.7784 | - |
459
- | 9.3475 | 51000 | 0.0909 | 0.5820 | 0.7771 | - |
460
- | 9.5308 | 52000 | 0.0919 | 0.5589 | 0.7814 | - |
461
- | 9.7141 | 53000 | 0.0939 | 0.5521 | 0.7815 | - |
462
- | 9.8974 | 54000 | 0.0925 | 0.6942 | 0.7826 | - |
463
- | 10.0806 | 55000 | 0.0863 | 0.6208 | 0.7805 | - |
464
- | 10.2639 | 56000 | 0.0803 | 0.6632 | 0.7628 | - |
465
- | 10.4472 | 57000 | 0.0797 | 0.6583 | 0.7718 | - |
466
- | 10.6305 | 58000 | 0.0824 | 0.6194 | 0.7842 | - |
467
- | 10.8138 | 59000 | 0.0829 | 0.6136 | 0.7846 | - |
468
- | 10.9971 | 60000 | 0.0819 | 0.5833 | 0.7874 | - |
469
- | 11.1804 | 61000 | 0.0693 | 0.6491 | 0.7847 | - |
470
- | 11.3636 | 62000 | 0.0709 | 0.6449 | 0.7901 | - |
471
- | 11.5469 | 63000 | 0.0721 | 0.6158 | 0.7788 | - |
472
- | 11.7302 | 64000 | 0.0721 | 0.6649 | 0.7857 | - |
473
- | 11.9135 | 65000 | 0.0732 | 0.6403 | 0.7858 | - |
474
- | 12.0968 | 66000 | 0.0679 | 0.6079 | 0.7752 | - |
475
- | 12.2801 | 67000 | 0.0615 | 0.6862 | 0.7890 | - |
476
- | 12.4633 | 68000 | 0.0629 | 0.7239 | 0.7860 | - |
477
- | 12.6466 | 69000 | 0.0643 | 0.6419 | 0.7847 | - |
478
- | 12.8299 | 70000 | 0.0635 | 0.6743 | 0.7885 | - |
479
- | 13.0132 | 71000 | 0.064 | 0.7135 | 0.7904 | - |
480
- | 13.1965 | 72000 | 0.0545 | 0.6643 | 0.7870 | - |
481
- | 13.3798 | 73000 | 0.0548 | 0.6508 | 0.7885 | - |
482
- | 13.5630 | 74000 | 0.0547 | 0.7003 | 0.7872 | - |
483
- | 13.7463 | 75000 | 0.0548 | 0.7170 | 0.7786 | - |
484
- | 13.9296 | 76000 | 0.0553 | 0.6917 | 0.7800 | - |
485
- | 14.1129 | 77000 | 0.0508 | 0.7000 | 0.7891 | - |
486
- | 14.2962 | 78000 | 0.0474 | 0.7336 | 0.7910 | - |
487
- | 14.4795 | 79000 | 0.0465 | 0.7122 | 0.7880 | - |
488
- | 14.6628 | 80000 | 0.0478 | 0.7321 | 0.7845 | - |
489
- | 14.8460 | 81000 | 0.0468 | 0.7112 | 0.7819 | - |
490
- | 15.0293 | 82000 | 0.0465 | 0.7534 | 0.7884 | - |
491
- | 15.2126 | 83000 | 0.0395 | 0.7238 | 0.7826 | - |
492
- | 15.3959 | 84000 | 0.0401 | 0.7686 | 0.7752 | - |
493
- | 15.5792 | 85000 | 0.0408 | 0.7296 | 0.7840 | - |
494
- | 15.7625 | 86000 | 0.0414 | 0.7533 | 0.7819 | - |
495
- | 15.9457 | 87000 | 0.0402 | 0.7748 | 0.7802 | - |
496
- | 16.1290 | 88000 | 0.0352 | 0.8267 | 0.7770 | - |
497
- | 16.3123 | 89000 | 0.0354 | 0.7488 | 0.7829 | - |
498
- | 16.4956 | 90000 | 0.0337 | 0.7850 | 0.7753 | - |
499
- | 16.6789 | 91000 | 0.0333 | 0.7812 | 0.7835 | - |
500
- | 16.8622 | 92000 | 0.0341 | 0.8184 | 0.7791 | - |
501
- | 17.0455 | 93000 | 0.0333 | 0.8166 | 0.7791 | - |
502
- | 17.2287 | 94000 | 0.0288 | 0.7980 | 0.7775 | - |
503
- | 17.4120 | 95000 | 0.0282 | 0.8195 | 0.7788 | - |
504
- | 17.5953 | 96000 | 0.0285 | 0.7864 | 0.7770 | - |
505
- | 17.7786 | 97000 | 0.0284 | 0.8000 | 0.7812 | - |
506
- | 17.9619 | 98000 | 0.0279 | 0.8118 | 0.7808 | - |
507
- | 18.1452 | 99000 | 0.0245 | 0.8727 | 0.7820 | - |
508
- | 18.3284 | 100000 | 0.0235 | 0.8695 | 0.7778 | - |
509
- | 18.5117 | 101000 | 0.0236 | 0.8246 | 0.7825 | - |
510
- | 18.6950 | 102000 | 0.0232 | 0.8543 | 0.7847 | - |
511
- | 18.8783 | 103000 | 0.0234 | 0.8840 | 0.7842 | - |
512
- | 19.0616 | 104000 | 0.0219 | 0.8804 | 0.7860 | - |
513
- | 19.2449 | 105000 | 0.0201 | 0.8885 | 0.7846 | - |
514
- | 19.4282 | 106000 | 0.0194 | 0.8901 | 0.7881 | - |
515
- | 19.6114 | 107000 | 0.0197 | 0.8850 | 0.7863 | - |
516
- | 19.7947 | 108000 | 0.0196 | 0.8835 | 0.7860 | - |
517
- | 19.9780 | 109000 | 0.0197 | 0.8803 | 0.7859 | - |
518
 
519
  * The bold row denotes the saved checkpoint.
520
  </details>
 
38
  type: val
39
  metrics:
40
  - type: accuracy
41
+ value: 0.773111243307555
42
  name: Accuracy
43
  - type: accuracy_threshold
44
+ value: 0.7637044787406921
45
  name: Accuracy Threshold
46
  - type: f1
47
+ value: 0.6950724637681159
48
  name: F1
49
  - type: f1_threshold
50
+ value: 0.04638597369194031
51
  name: F1 Threshold
52
  - type: precision
53
+ value: 0.6454912516823688
54
  name: Precision
55
  - type: recall
56
+ value: 0.7529042386185243
57
  name: Recall
58
  - type: average_precision
59
+ value: 0.7833280130154174
60
  name: Average Precision
61
  - task:
62
  type: cross-encoder-classification
 
188
 
189
  | Metric | val | test |
190
  |:----------------------|:-----------|:-----------|
191
+ | accuracy | 0.7731 | 0.723 |
192
+ | accuracy_threshold | 0.7637 | 0.9352 |
193
+ | f1 | 0.6951 | 0.7144 |
194
+ | f1_threshold | 0.0464 | 0.9143 |
195
+ | precision | 0.6455 | 0.6303 |
196
+ | recall | 0.7529 | 0.8245 |
197
+ | **average_precision** | **0.7833** | **0.6907** |
198
 
199
  <!--
200
  ## Bias, Risks and Limitations
 
325
  - `bf16_full_eval`: False
326
  - `fp16_full_eval`: False
327
  - `tf32`: None
328
+ - `local_rank`: 0
329
  - `ddp_backend`: None
330
  - `tpu_num_cores`: None
331
  - `tpu_metrics_debug`: False
 
406
  | Epoch | Step | Training Loss | Validation Loss | val_average_precision | test_average_precision |
407
  |:----------:|:--------:|:-------------:|:---------------:|:---------------------:|:----------------------:|
408
  | -1 | -1 | - | - | 0.7676 | 0.6907 |
409
+ | 0.1833 | 1000 | 0.3563 | 0.4805 | 0.7831 | - |
410
+ | **0.3666** | **2000** | **0.2065** | **0.5394** | **0.8221** | **-** |
411
+ | 0.5499 | 3000 | 0.1983 | 0.5019 | 0.8178 | - |
412
+ | 0.7331 | 4000 | 0.1923 | 0.5109 | 0.7960 | - |
413
+ | 0.9164 | 5000 | 0.1886 | 0.4726 | 0.8058 | - |
414
+ | 1.0997 | 6000 | 0.183 | 0.5062 | 0.8032 | - |
415
+ | 1.2830 | 7000 | 0.1838 | 0.5152 | 0.8021 | - |
416
+ | 1.4663 | 8000 | 0.1858 | 0.5105 | 0.7926 | - |
417
+ | 1.6496 | 9000 | 0.1905 | 0.5052 | 0.7859 | - |
418
+ | 1.8328 | 10000 | 0.1926 | 0.5316 | 0.7895 | - |
419
+ | 2.0161 | 11000 | 0.1951 | 0.5340 | 0.7681 | - |
420
+ | 2.1994 | 12000 | 0.1853 | 0.5573 | 0.7577 | - |
421
+ | 2.3827 | 13000 | 0.1848 | 0.5530 | 0.7946 | - |
422
+ | 2.5660 | 14000 | 0.1813 | 0.5754 | 0.7655 | - |
423
+ | 2.7493 | 15000 | 0.1793 | 0.5316 | 0.7514 | - |
424
+ | 2.9326 | 16000 | 0.1778 | 0.5230 | 0.7868 | - |
425
+ | 3.1158 | 17000 | 0.1681 | 0.5246 | 0.7816 | - |
426
+ | 3.2991 | 18000 | 0.1662 | 0.4946 | 0.7732 | - |
427
+ | 3.4824 | 19000 | 0.1648 | 0.5262 | 0.7853 | - |
428
+ | 3.6657 | 20000 | 0.1649 | 0.5007 | 0.7871 | - |
429
+ | 3.8490 | 21000 | 0.1633 | 0.5368 | 0.7807 | - |
430
+ | 4.0323 | 22000 | 0.1602 | 0.5559 | 0.7769 | - |
431
+ | 4.2155 | 23000 | 0.149 | 0.5796 | 0.7697 | - |
432
+ | 4.3988 | 24000 | 0.1486 | 0.5322 | 0.7608 | - |
433
+ | 4.5821 | 25000 | 0.1495 | 0.5142 | 0.7713 | - |
434
  | 4.7654 | 26000 | 0.1493 | 0.5203 | 0.7866 | - |
435
+ | 4.9487 | 27000 | 0.1498 | 0.5433 | 0.7738 | - |
436
+ | 5.1320 | 28000 | 0.1391 | 0.5589 | 0.7803 | - |
437
+ | 5.3152 | 29000 | 0.1346 | 0.5267 | 0.7713 | - |
438
+ | 5.4985 | 30000 | 0.1367 | 0.5657 | 0.7803 | - |
439
+ | 5.6818 | 31000 | 0.1358 | 0.5631 | 0.7646 | - |
440
+ | 5.8651 | 32000 | 0.136 | 0.5444 | 0.7753 | - |
441
+ | 6.0484 | 33000 | 0.1346 | 0.5605 | 0.7703 | - |
442
+ | 6.2317 | 34000 | 0.1222 | 0.5399 | 0.7776 | - |
443
+ | 6.4150 | 35000 | 0.1241 | 0.5272 | 0.7899 | - |
444
+ | 6.5982 | 36000 | 0.1243 | 0.6096 | 0.7723 | - |
445
+ | 6.7815 | 37000 | 0.1266 | 0.5661 | 0.7609 | - |
446
+ | 6.9648 | 38000 | 0.1246 | 0.5341 | 0.7889 | - |
447
+ | 7.1481 | 39000 | 0.1128 | 0.6223 | 0.7884 | - |
448
+ | 7.3314 | 40000 | 0.1124 | 0.5485 | 0.7743 | - |
449
+ | 7.5147 | 41000 | 0.1127 | 0.5375 | 0.7842 | - |
450
+ | 7.6979 | 42000 | 0.1122 | 0.5231 | 0.7939 | - |
451
+ | 7.8812 | 43000 | 0.1141 | 0.5608 | 0.7705 | - |
452
+ | 8.0645 | 44000 | 0.1088 | 0.6511 | 0.7813 | - |
453
+ | 8.2478 | 45000 | 0.0998 | 0.6217 | 0.7648 | - |
454
+ | 8.4311 | 46000 | 0.1017 | 0.6000 | 0.7822 | - |
455
+ | 8.6144 | 47000 | 0.1031 | 0.5469 | 0.7866 | - |
456
+ | 8.7977 | 48000 | 0.1012 | 0.5862 | 0.7790 | - |
457
+ | 8.9809 | 49000 | 0.1031 | 0.5527 | 0.7876 | - |
458
+ | 9.1642 | 50000 | 0.0921 | 0.5460 | 0.7788 | - |
459
+ | 9.3475 | 51000 | 0.0909 | 0.5820 | 0.7815 | - |
460
+ | 9.5308 | 52000 | 0.0919 | 0.5589 | 0.7841 | - |
461
+ | 9.7141 | 53000 | 0.0939 | 0.5521 | 0.7821 | - |
462
+ | 9.8974 | 54000 | 0.0925 | 0.6942 | 0.7797 | - |
463
+ | 10.0806 | 55000 | 0.0863 | 0.6208 | 0.7729 | - |
464
+ | 10.2639 | 56000 | 0.0803 | 0.6632 | 0.7911 | - |
465
+ | 10.4472 | 57000 | 0.0797 | 0.6583 | 0.7833 | - |
466
+ | 10.6305 | 58000 | 0.0824 | 0.6194 | 0.7862 | - |
467
+ | 10.8138 | 59000 | 0.0829 | 0.6136 | 0.7783 | - |
468
+ | 10.9971 | 60000 | 0.0819 | 0.5833 | 0.7727 | - |
469
+ | 11.1804 | 61000 | 0.0693 | 0.6491 | 0.7881 | - |
470
+ | 11.3636 | 62000 | 0.0709 | 0.6449 | 0.7784 | - |
471
+ | 11.5469 | 63000 | 0.0721 | 0.6158 | 0.7838 | - |
472
+ | 11.7302 | 64000 | 0.0721 | 0.6649 | 0.7841 | - |
473
+ | 11.9135 | 65000 | 0.0732 | 0.6403 | 0.7702 | - |
474
+ | 12.0968 | 66000 | 0.0679 | 0.6079 | 0.7817 | - |
475
+ | 12.2801 | 67000 | 0.0615 | 0.6862 | 0.7787 | - |
476
+ | 12.4633 | 68000 | 0.0629 | 0.7239 | 0.7824 | - |
477
+ | 12.6466 | 69000 | 0.0643 | 0.6419 | 0.7897 | - |
478
+ | 12.8299 | 70000 | 0.0635 | 0.6743 | 0.7762 | - |
479
+ | 13.0132 | 71000 | 0.064 | 0.7135 | 0.7741 | - |
480
+ | 13.1965 | 72000 | 0.0545 | 0.6643 | 0.7723 | - |
481
+ | 13.3798 | 73000 | 0.0548 | 0.6508 | 0.7758 | - |
482
+ | 13.5630 | 74000 | 0.0547 | 0.7003 | 0.7785 | - |
483
+ | 13.7463 | 75000 | 0.0548 | 0.7170 | 0.7846 | - |
484
+ | 13.9296 | 76000 | 0.0553 | 0.6917 | 0.7722 | - |
485
+ | 14.1129 | 77000 | 0.0508 | 0.7000 | 0.7767 | - |
486
+ | 14.2962 | 78000 | 0.0474 | 0.7336 | 0.7730 | - |
487
+ | 14.4795 | 79000 | 0.0465 | 0.7122 | 0.7795 | - |
488
+ | 14.6628 | 80000 | 0.0478 | 0.7321 | 0.7779 | - |
489
+ | 14.8460 | 81000 | 0.0468 | 0.7112 | 0.7796 | - |
490
+ | 15.0293 | 82000 | 0.0465 | 0.7534 | 0.7788 | - |
491
+ | 15.2126 | 83000 | 0.0395 | 0.7238 | 0.7808 | - |
492
+ | 15.3959 | 84000 | 0.0401 | 0.7686 | 0.7905 | - |
493
+ | 15.5792 | 85000 | 0.0408 | 0.7296 | 0.7900 | - |
494
+ | 15.7625 | 86000 | 0.0414 | 0.7533 | 0.7822 | - |
495
+ | 15.9457 | 87000 | 0.0402 | 0.7748 | 0.7867 | - |
496
+ | 16.1290 | 88000 | 0.0352 | 0.8267 | 0.7844 | - |
497
+ | 16.3123 | 89000 | 0.0354 | 0.7488 | 0.7912 | - |
498
+ | 16.4956 | 90000 | 0.0337 | 0.7850 | 0.7857 | - |
499
+ | 16.6789 | 91000 | 0.0333 | 0.7812 | 0.7815 | - |
500
+ | 16.8622 | 92000 | 0.0341 | 0.8184 | 0.7786 | - |
501
+ | 17.0455 | 93000 | 0.0333 | 0.8166 | 0.7781 | - |
502
+ | 17.2287 | 94000 | 0.0288 | 0.7980 | 0.7803 | - |
503
+ | 17.4120 | 95000 | 0.0282 | 0.8195 | 0.7774 | - |
504
+ | 17.5953 | 96000 | 0.0285 | 0.7864 | 0.7829 | - |
505
+ | 17.7786 | 97000 | 0.0284 | 0.8000 | 0.7838 | - |
506
+ | 17.9619 | 98000 | 0.0279 | 0.8118 | 0.7873 | - |
507
+ | 18.1452 | 99000 | 0.0245 | 0.8727 | 0.7866 | - |
508
+ | 18.3284 | 100000 | 0.0235 | 0.8695 | 0.7836 | - |
509
+ | 18.5117 | 101000 | 0.0236 | 0.8246 | 0.7820 | - |
510
+ | 18.6950 | 102000 | 0.0232 | 0.8543 | 0.7828 | - |
511
+ | 18.8783 | 103000 | 0.0234 | 0.8840 | 0.7793 | - |
512
+ | 19.0616 | 104000 | 0.0219 | 0.8804 | 0.7783 | - |
513
+ | 19.2449 | 105000 | 0.0201 | 0.8885 | 0.7812 | - |
514
+ | 19.4282 | 106000 | 0.0194 | 0.8901 | 0.7821 | - |
515
+ | 19.6114 | 107000 | 0.0197 | 0.8850 | 0.7824 | - |
516
+ | 19.7947 | 108000 | 0.0196 | 0.8835 | 0.7830 | - |
517
+ | 19.9780 | 109000 | 0.0197 | 0.8803 | 0.7833 | - |
518
 
519
  * The bold row denotes the saved checkpoint.
520
  </details>
model.safetensors CHANGED
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