napsternxg commited on
Commit
25ad7c7
1 Parent(s): 69c0828

End of training

Browse files
README.md CHANGED
@@ -16,16 +16,16 @@ should probably proofread and complete it, then remove this comment. -->
16
 
17
  This model is a fine-tuned version of [napsternxg/gte-small-L3-ingredient-v2](https://huggingface.co/napsternxg/gte-small-L3-ingredient-v2) on the nyt_ingredients dataset.
18
  It achieves the following results on the evaluation set:
19
- - Loss: 2.5723
20
- - Comment: {'precision': 0.6705310396409873, 'recall': 0.7578191039729502, 'f1': 0.7115079365079365, 'number': 7098}
21
- - Name: {'precision': 0.8150406504065041, 'recall': 0.8209244693459756, 'f1': 0.8179719791722584, 'number': 9281}
22
- - Qty: {'precision': 0.9861000794281175, 'recall': 0.9857086145295753, 'f1': 0.9859043081199126, 'number': 7557}
23
- - Range End: {'precision': 0.5986842105263158, 'recall': 0.9479166666666666, 'f1': 0.7338709677419355, 'number': 96}
24
- - Unit: {'precision': 0.9225395839801304, 'recall': 0.985735611212473, 'f1': 0.9530911715179216, 'number': 6029}
25
- - Overall Precision: 0.8402
26
- - Overall Recall: 0.8809
27
- - Overall F1: 0.8601
28
- - Overall Accuracy: 0.8330
29
 
30
  ## Model description
31
 
@@ -50,27 +50,62 @@ The following hyperparameters were used during training:
50
  - seed: 42
51
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
52
  - lr_scheduler_type: linear
53
- - num_epochs: 3
54
 
55
  ### Training results
56
 
57
- | Training Loss | Epoch | Step | Validation Loss | Comment | Name | Qty | Range End | Unit | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
58
- |:-------------:|:-----:|:-----:|:---------------:|:---------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
59
- | 4.174 | 0.2 | 1000 | 3.8690 | {'precision': 0.5304157015725954, 'recall': 0.6285755561976307, 'f1': 0.5753388429752067, 'number': 6922} | {'precision': 0.7673592421143288, 'recall': 0.8069738480697385, 'f1': 0.7866681381745945, 'number': 8833} | {'precision': 0.9667778704475952, 'recall': 0.9806824591088551, 'f1': 0.9736805263894722, 'number': 7092} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 88} | {'precision': 0.9121887287024901, 'recall': 0.9756439460311898, 'f1': 0.9428498856997714, 'number': 5707} | 0.7795 | 0.8380 | 0.8077 | 0.7962 |
60
- | 3.5528 | 0.4 | 2000 | 3.4154 | {'precision': 0.5496301598663803, 'recall': 0.6655590869690841, 'f1': 0.6020648196549921, 'number': 6922} | {'precision': 0.7787928221859707, 'recall': 0.8107098381070984, 'f1': 0.7944308852895496, 'number': 8833} | {'precision': 0.9785673998871969, 'recall': 0.9785673998871969, 'f1': 0.9785673998871969, 'number': 7092} | {'precision': 0.6666666666666666, 'recall': 0.13636363636363635, 'f1': 0.22641509433962262, 'number': 88} | {'precision': 0.9109700520833334, 'recall': 0.9807254249167688, 'f1': 0.9445616403679015, 'number': 5707} | 0.7887 | 0.8490 | 0.8177 | 0.8042 |
61
- | 3.3333 | 0.59 | 3000 | 3.1915 | {'precision': 0.5850767928407304, 'recall': 0.6989309448136377, 'f1': 0.6369560924231453, 'number': 6922} | {'precision': 0.7759810263044415, 'recall': 0.814898675421714, 'f1': 0.7949638301397095, 'number': 8833} | {'precision': 0.9797125950972105, 'recall': 0.9805414551607445, 'f1': 0.9801268498942918, 'number': 7092} | {'precision': 0.6867469879518072, 'recall': 0.6477272727272727, 'f1': 0.6666666666666667, 'number': 88} | {'precision': 0.9255372313843079, 'recall': 0.9735412651130191, 'f1': 0.948932536293766, 'number': 5707} | 0.8006 | 0.8590 | 0.8288 | 0.8124 |
62
- | 3.1122 | 0.79 | 4000 | 3.0560 | {'precision': 0.6020151133501259, 'recall': 0.7250794568043918, 'f1': 0.6578412740022282, 'number': 6922} | {'precision': 0.7925502692011867, 'recall': 0.8165968527114231, 'f1': 0.8043938887030222, 'number': 8833} | {'precision': 0.9816358242689646, 'recall': 0.9798364354201917, 'f1': 0.9807353044950956, 'number': 7092} | {'precision': 0.5547445255474452, 'recall': 0.8636363636363636, 'f1': 0.6755555555555556, 'number': 88} | {'precision': 0.9180758496141849, 'recall': 0.9798493078675311, 'f1': 0.9479572808950669, 'number': 5707} | 0.8082 | 0.8676 | 0.8368 | 0.8183 |
63
- | 3.074 | 0.99 | 5000 | 2.9495 | {'precision': 0.6171328671328671, 'recall': 0.7139555041895406, 'f1': 0.6620227729403884, 'number': 6922} | {'precision': 0.8028043623414199, 'recall': 0.816710064530737, 'f1': 0.8096975138896684, 'number': 8833} | {'precision': 0.9747242005306521, 'recall': 0.9842075578116187, 'f1': 0.9794429242966393, 'number': 7092} | {'precision': 0.6448598130841121, 'recall': 0.7840909090909091, 'f1': 0.7076923076923077, 'number': 88} | {'precision': 0.9168310322156475, 'recall': 0.9773961801296653, 'f1': 0.9461453651089815, 'number': 5707} | 0.8167 | 0.8653 | 0.8403 | 0.8209 |
64
- | 2.936 | 1.19 | 6000 | 2.8893 | {'precision': 0.6245376865195765, 'recall': 0.7074544929211211, 'f1': 0.6634152949942423, 'number': 6922} | {'precision': 0.8003099402258136, 'recall': 0.81852145363976, 'f1': 0.8093132590809874, 'number': 8833} | {'precision': 0.9721951897678298, 'recall': 0.9860406091370558, 'f1': 0.9790689534476724, 'number': 7092} | {'precision': 0.6220472440944882, 'recall': 0.8977272727272727, 'f1': 0.7348837209302326, 'number': 88} | {'precision': 0.9140714169248328, 'recall': 0.9823024356053969, 'f1': 0.9469594594594595, 'number': 5707} | 0.8179 | 0.8660 | 0.8413 | 0.8217 |
65
- | 2.7662 | 1.39 | 7000 | 2.8622 | {'precision': 0.6298537569339385, 'recall': 0.7217567177116441, 'f1': 0.6726807593914097, 'number': 6922} | {'precision': 0.7999777753083676, 'recall': 0.8150118872410279, 'f1': 0.8074248541947062, 'number': 8833} | {'precision': 0.9800337457817773, 'recall': 0.9827975183305132, 'f1': 0.9814136862855534, 'number': 7092} | {'precision': 0.6290322580645161, 'recall': 0.8863636363636364, 'f1': 0.7358490566037735, 'number': 88} | {'precision': 0.9191902567478605, 'recall': 0.9786227439985982, 'f1': 0.9479758974794195, 'number': 5707} | 0.8210 | 0.8668 | 0.8433 | 0.8235 |
66
- | 2.7839 | 1.58 | 8000 | 2.7801 | {'precision': 0.6325475860330266, 'recall': 0.7249349898873158, 'f1': 0.6755974419387412, 'number': 6922} | {'precision': 0.8036190053285968, 'recall': 0.8195403600135854, 'f1': 0.8115015974440895, 'number': 8833} | {'precision': 0.975977653631285, 'recall': 0.9853355893965031, 'f1': 0.9806342969407802, 'number': 7092} | {'precision': 0.6521739130434783, 'recall': 0.8522727272727273, 'f1': 0.7389162561576356, 'number': 88} | {'precision': 0.9188301018731515, 'recall': 0.9798493078675311, 'f1': 0.9483591961332994, 'number': 5707} | 0.8221 | 0.8698 | 0.8453 | 0.8242 |
67
- | 2.7221 | 1.78 | 9000 | 2.7520 | {'precision': 0.6436781609195402, 'recall': 0.7442935567754985, 'f1': 0.690339005761758, 'number': 6922} | {'precision': 0.8124719605204127, 'recall': 0.8201064191101551, 'f1': 0.8162713392303792, 'number': 8833} | {'precision': 0.9827975183305132, 'recall': 0.9827975183305132, 'f1': 0.9827975183305132, 'number': 7092} | {'precision': 0.6576576576576577, 'recall': 0.8295454545454546, 'f1': 0.7336683417085428, 'number': 88} | {'precision': 0.9227716222920457, 'recall': 0.9777466269493604, 'f1': 0.9494640122511486, 'number': 5707} | 0.8293 | 0.8735 | 0.8508 | 0.8285 |
68
- | 2.7156 | 1.98 | 10000 | 2.7236 | {'precision': 0.6453828542355635, 'recall': 0.7330251372435712, 'f1': 0.6864177489177489, 'number': 6922} | {'precision': 0.8084821428571428, 'recall': 0.8201064191101551, 'f1': 0.8142527960433878, 'number': 8833} | {'precision': 0.9825204398082887, 'recall': 0.9827975183305132, 'f1': 0.9826589595375722, 'number': 7092} | {'precision': 0.6324786324786325, 'recall': 0.8409090909090909, 'f1': 0.7219512195121951, 'number': 88} | {'precision': 0.9222387320455672, 'recall': 0.9787979674084458, 'f1': 0.9496769806188372, 'number': 5707} | 0.8291 | 0.8710 | 0.8496 | 0.8265 |
69
- | 2.6804 | 2.18 | 11000 | 2.6929 | {'precision': 0.6422784494578088, 'recall': 0.7444380236925744, 'f1': 0.6895951823352291, 'number': 6922} | {'precision': 0.8120670391061453, 'recall': 0.8228235027736895, 'f1': 0.8174098858460327, 'number': 8833} | {'precision': 0.9837570621468926, 'recall': 0.9820924985899605, 'f1': 0.9829240756421113, 'number': 7092} | {'precision': 0.635593220338983, 'recall': 0.8522727272727273, 'f1': 0.7281553398058253, 'number': 88} | {'precision': 0.9234584228798148, 'recall': 0.9787979674084458, 'f1': 0.9503232391970058, 'number': 5707} | 0.8288 | 0.8745 | 0.8510 | 0.8279 |
70
- | 2.6121 | 2.38 | 12000 | 2.6691 | {'precision': 0.6490939044481054, 'recall': 0.7399595492632187, 'f1': 0.691554715452643, 'number': 6922} | {'precision': 0.811037725288257, 'recall': 0.820219630929469, 'f1': 0.8156028368794326, 'number': 8833} | {'precision': 0.9798121407542408, 'recall': 0.9854765933446137, 'f1': 0.9826362038664324, 'number': 7092} | {'precision': 0.6328125, 'recall': 0.9204545454545454, 'f1': 0.7499999999999999, 'number': 88} | {'precision': 0.9207106431978944, 'recall': 0.9807254249167688, 'f1': 0.9497709146444936, 'number': 5707} | 0.8299 | 0.8740 | 0.8514 | 0.8277 |
71
- | 2.553 | 2.57 | 13000 | 2.6652 | {'precision': 0.6478233438485804, 'recall': 0.7416931522681306, 'f1': 0.6915875260995488, 'number': 6922} | {'precision': 0.8128150554497592, 'recall': 0.8214649609419223, 'f1': 0.8171171171171171, 'number': 8833} | {'precision': 0.9826760563380281, 'recall': 0.983784545967287, 'f1': 0.9832299887260428, 'number': 7092} | {'precision': 0.639344262295082, 'recall': 0.8863636363636364, 'f1': 0.742857142857143, 'number': 88} | {'precision': 0.920335085413929, 'recall': 0.9817767653758542, 'f1': 0.9500635862653668, 'number': 5707} | 0.8304 | 0.8745 | 0.8519 | 0.8287 |
72
- | 2.5781 | 2.77 | 14000 | 2.6431 | {'precision': 0.6512514292974209, 'recall': 0.7405374169315226, 'f1': 0.6930304873926858, 'number': 6922} | {'precision': 0.8114304887596465, 'recall': 0.8213517491226084, 'f1': 0.8163609767075503, 'number': 8833} | {'precision': 0.9832252607837609, 'recall': 0.983502538071066, 'f1': 0.9833638798815735, 'number': 7092} | {'precision': 0.6551724137931034, 'recall': 0.8636363636363636, 'f1': 0.7450980392156864, 'number': 88} | {'precision': 0.9220500988793672, 'recall': 0.9803749780970737, 'f1': 0.9503184713375797, 'number': 5707} | 0.8317 | 0.8738 | 0.8522 | 0.8286 |
73
- | 2.5928 | 2.97 | 15000 | 2.6394 | {'precision': 0.6551064643631264, 'recall': 0.7422710199364345, 'f1': 0.6959701997968167, 'number': 6922} | {'precision': 0.8126049479458188, 'recall': 0.8218045963998641, 'f1': 0.8171788810086682, 'number': 8833} | {'precision': 0.9825376707505985, 'recall': 0.983784545967287, 'f1': 0.9831607130275488, 'number': 7092} | {'precision': 0.6470588235294118, 'recall': 0.875, 'f1': 0.7439613526570048, 'number': 88} | {'precision': 0.9219729462223688, 'recall': 0.9793236376379885, 'f1': 0.9497833290848839, 'number': 5707} | 0.8331 | 0.8742 | 0.8532 | 0.8289 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
74
 
75
 
76
  ### Framework versions
 
16
 
17
  This model is a fine-tuned version of [napsternxg/gte-small-L3-ingredient-v2](https://huggingface.co/napsternxg/gte-small-L3-ingredient-v2) on the nyt_ingredients dataset.
18
  It achieves the following results on the evaluation set:
19
+ - Loss: 2.0746
20
+ - Comment: {'precision': 0.7012264508787457, 'recall': 0.7701708096097765, 'f1': 0.7340833884844474, 'number': 7201}
21
+ - Name: {'precision': 0.8148584905660378, 'recall': 0.8195148247978437, 'f1': 0.8171800247271946, 'number': 9275}
22
+ - Qty: {'precision': 0.9843189368770764, 'recall': 0.9881270010672358, 'f1': 0.9862192929898143, 'number': 7496}
23
+ - Range End: {'precision': 0.6535947712418301, 'recall': 0.9259259259259259, 'f1': 0.7662835249042146, 'number': 108}
24
+ - Unit: {'precision': 0.9298190892077355, 'recall': 0.9854545454545455, 'f1': 0.9568287594286632, 'number': 6050}
25
+ - Overall Precision: 0.8496
26
+ - Overall Recall: 0.8834
27
+ - Overall F1: 0.8662
28
+ - Overall Accuracy: 0.8372
29
 
30
  ## Model description
31
 
 
50
  - seed: 42
51
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
52
  - lr_scheduler_type: linear
53
+ - num_epochs: 10
54
 
55
  ### Training results
56
 
57
+ | Training Loss | Epoch | Step | Validation Loss | Comment | Name | Qty | Range End | Unit | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
58
+ |:-------------:|:-----:|:-----:|:---------------:|:---------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
59
+ | 4.134 | 0.2 | 1000 | 3.7771 | {'precision': 0.5343387760189455, 'recall': 0.6254741756638459, 'f1': 0.5763258721516435, 'number': 6854} | {'precision': 0.7608440797186401, 'recall': 0.8071226681741097, 'f1': 0.78330041694097, 'number': 8845} | {'precision': 0.960741548527808, 'recall': 0.9854586129753915, 'f1': 0.9729431253451132, 'number': 7152} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 105} | {'precision': 0.921378387420542, 'recall': 0.975557917109458, 'f1': 0.9476944253269098, 'number': 5646} | 0.7807 | 0.8385 | 0.8085 | 0.7949 |
60
+ | 3.5226 | 0.4 | 2000 | 3.3655 | {'precision': 0.5741313218746136, 'recall': 0.6774146483805077, 'f1': 0.6215112776922562, 'number': 6854} | {'precision': 0.7699133967710895, 'recall': 0.8141322781232334, 'f1': 0.7914056489724146, 'number': 8845} | {'precision': 0.9728388253136633, 'recall': 0.9865771812080537, 'f1': 0.9796598403332176, 'number': 7152} | {'precision': 0.6120689655172413, 'recall': 0.6761904761904762, 'f1': 0.6425339366515838, 'number': 105} | {'precision': 0.9102040816326531, 'recall': 0.9874247254693589, 'f1': 0.9472432248746921, 'number': 5646} | 0.7935 | 0.8582 | 0.8246 | 0.8064 |
61
+ | 3.1948 | 0.59 | 3000 | 3.1104 | {'precision': 0.6045112781954888, 'recall': 0.7038225853516195, 'f1': 0.6503977349332615, 'number': 6854} | {'precision': 0.7898614471079833, 'recall': 0.8120972300734879, 'f1': 0.8008250181169521, 'number': 8845} | {'precision': 0.9832167832167832, 'recall': 0.9829418344519015, 'f1': 0.9830792896098447, 'number': 7152} | {'precision': 0.6013513513513513, 'recall': 0.8476190476190476, 'f1': 0.7035573122529643, 'number': 105} | {'precision': 0.9178104845377874, 'recall': 0.9829968119022316, 'f1': 0.9492858975455399, 'number': 5646} | 0.8112 | 0.8627 | 0.8362 | 0.8160 |
62
+ | 3.0233 | 0.79 | 4000 | 3.0053 | {'precision': 0.6183673469387755, 'recall': 0.7073241902538664, 'f1': 0.6598611678236015, 'number': 6854} | {'precision': 0.8008859357696567, 'recall': 0.8176370830977954, 'f1': 0.8091748251748251, 'number': 8845} | {'precision': 0.982826026249651, 'recall': 0.9842002237136466, 'f1': 0.9835126449629734, 'number': 7152} | {'precision': 0.6626506024096386, 'recall': 0.5238095238095238, 'f1': 0.5851063829787234, 'number': 105} | {'precision': 0.9206639004149377, 'recall': 0.9824654622741764, 'f1': 0.9505612201182417, 'number': 5646} | 0.8202 | 0.8643 | 0.8417 | 0.8174 |
63
+ | 2.9567 | 0.99 | 5000 | 2.9100 | {'precision': 0.633295267098084, 'recall': 0.7281879194630873, 'f1': 0.677434679334917, 'number': 6854} | {'precision': 0.8036823425022183, 'recall': 0.8192198982475976, 'f1': 0.8113767426235933, 'number': 8845} | {'precision': 0.9803757828810021, 'recall': 0.9848993288590604, 'f1': 0.9826323498639883, 'number': 7152} | {'precision': 0.6853932584269663, 'recall': 0.580952380952381, 'f1': 0.6288659793814434, 'number': 105} | {'precision': 0.9114089571755476, 'recall': 0.9876018420120439, 'f1': 0.9479768786127167, 'number': 5646} | 0.8227 | 0.8712 | 0.8462 | 0.8216 |
64
+ | 2.738 | 1.19 | 6000 | 2.8514 | {'precision': 0.6383489017924766, 'recall': 0.7378173329442661, 'f1': 0.6844883595018949, 'number': 6854} | {'precision': 0.8046195045748716, 'recall': 0.8152628603730921, 'f1': 0.809906216656371, 'number': 8845} | {'precision': 0.9762201023088621, 'recall': 0.9872762863534675, 'f1': 0.9817170663885992, 'number': 7152} | {'precision': 0.6143790849673203, 'recall': 0.8952380952380953, 'f1': 0.7286821705426357, 'number': 105} | {'precision': 0.9254855994641661, 'recall': 0.9789231314204747, 'f1': 0.9514546393527284, 'number': 5646} | 0.8250 | 0.8723 | 0.8480 | 0.8213 |
65
+ | 2.8132 | 1.39 | 7000 | 2.7760 | {'precision': 0.641124871001032, 'recall': 0.7251240151736212, 'f1': 0.680542242913871, 'number': 6854} | {'precision': 0.8001110494169905, 'recall': 0.814584511023177, 'f1': 0.8072829131652661, 'number': 8845} | {'precision': 0.9824365765263451, 'recall': 0.9854586129753915, 'f1': 0.9839452743263996, 'number': 7152} | {'precision': 0.6291390728476821, 'recall': 0.9047619047619048, 'f1': 0.7421875, 'number': 105} | {'precision': 0.9219787516600265, 'recall': 0.983705278072972, 'f1': 0.9518423307626392, 'number': 5646} | 0.8261 | 0.8696 | 0.8473 | 0.8223 |
66
+ | 2.6976 | 1.58 | 8000 | 2.7073 | {'precision': 0.6535493827160493, 'recall': 0.7414648380507732, 'f1': 0.6947368421052631, 'number': 6854} | {'precision': 0.8127884723629405, 'recall': 0.8162803843979649, 'f1': 0.8145306859205775, 'number': 8845} | {'precision': 0.9831147083449623, 'recall': 0.9850391498881432, 'f1': 0.9840759882665177, 'number': 7152} | {'precision': 0.6418918918918919, 'recall': 0.9047619047619048, 'f1': 0.75098814229249, 'number': 105} | {'precision': 0.926531975288028, 'recall': 0.9828196953595466, 'f1': 0.9538461538461539, 'number': 5646} | 0.8341 | 0.8738 | 0.8535 | 0.8262 |
67
+ | 2.6347 | 1.78 | 9000 | 2.6448 | {'precision': 0.6538461538461539, 'recall': 0.7416107382550335, 'f1': 0.6949685534591195, 'number': 6854} | {'precision': 0.8118188967531738, 'recall': 0.8169587337478802, 'f1': 0.8143807055111011, 'number': 8845} | {'precision': 0.9781375397813754, 'recall': 0.9883948545861297, 'f1': 0.9832394464149107, 'number': 7152} | {'precision': 0.6486486486486487, 'recall': 0.9142857142857143, 'f1': 0.7588932806324111, 'number': 105} | {'precision': 0.92432072012002, 'recall': 0.9821112291888062, 'f1': 0.9523400601116359, 'number': 5646} | 0.8326 | 0.8747 | 0.8531 | 0.8237 |
68
+ | 2.5847 | 1.98 | 10000 | 2.5910 | {'precision': 0.6645452134712277, 'recall': 0.7312518237525533, 'f1': 0.6963045290358433, 'number': 6854} | {'precision': 0.8138435565559933, 'recall': 0.8175240248728095, 'f1': 0.8156796390298928, 'number': 8845} | {'precision': 0.9793285238623751, 'recall': 0.986996644295302, 'f1': 0.9831476323119777, 'number': 7152} | {'precision': 0.6953125, 'recall': 0.8476190476190476, 'f1': 0.7639484978540773, 'number': 105} | {'precision': 0.9238443631526438, 'recall': 0.9840595111583422, 'f1': 0.9530017152658663, 'number': 5646} | 0.8378 | 0.8722 | 0.8547 | 0.8253 |
69
+ | 2.4321 | 2.18 | 11000 | 2.5732 | {'precision': 0.660557563242127, 'recall': 0.7467172454041435, 'f1': 0.7009998630324613, 'number': 6854} | {'precision': 0.8091286307053942, 'recall': 0.8157150932730356, 'f1': 0.8124085125548924, 'number': 8845} | {'precision': 0.9825516471245115, 'recall': 0.9842002237136466, 'f1': 0.9833752444816989, 'number': 7152} | {'precision': 0.6178343949044586, 'recall': 0.9238095238095239, 'f1': 0.7404580152671757, 'number': 105} | {'precision': 0.9210395629862606, 'recall': 0.9854764434998229, 'f1': 0.9521690767519465, 'number': 5646} | 0.8337 | 0.8752 | 0.8539 | 0.8255 |
70
+ | 2.4326 | 2.38 | 12000 | 2.5278 | {'precision': 0.6754826765405977, 'recall': 0.7452582433615407, 'f1': 0.7086570477247504, 'number': 6854} | {'precision': 0.8159918570459173, 'recall': 0.8157150932730356, 'f1': 0.8158534516876803, 'number': 8845} | {'precision': 0.9832635983263598, 'recall': 0.985738255033557, 'f1': 0.9844993715961456, 'number': 7152} | {'precision': 0.6739130434782609, 'recall': 0.8857142857142857, 'f1': 0.7654320987654321, 'number': 105} | {'precision': 0.9243306169965075, 'recall': 0.9844137442437123, 'f1': 0.9534265374388883, 'number': 5646} | 0.8419 | 0.8749 | 0.8581 | 0.8281 |
71
+ | 2.3705 | 2.57 | 13000 | 2.4819 | {'precision': 0.6670131219955827, 'recall': 0.7490516486723081, 'f1': 0.7056559686619477, 'number': 6854} | {'precision': 0.8106289942818702, 'recall': 0.8174109666478236, 'f1': 0.8140058545372664, 'number': 8845} | {'precision': 0.9827249930342714, 'recall': 0.9862975391498882, 'f1': 0.9845080251221213, 'number': 7152} | {'precision': 0.6111111111111112, 'recall': 0.9428571428571428, 'f1': 0.7415730337078652, 'number': 105} | {'precision': 0.9191769547325103, 'recall': 0.9890187743535246, 'f1': 0.952819725279413, 'number': 5646} | 0.8358 | 0.8776 | 0.8562 | 0.8270 |
72
+ | 2.364 | 2.77 | 14000 | 2.4206 | {'precision': 0.6672713138118683, 'recall': 0.7513860519404727, 'f1': 0.7068350260774088, 'number': 6854} | {'precision': 0.8101706331387517, 'recall': 0.8159412097230073, 'f1': 0.8130456824198727, 'number': 8845} | {'precision': 0.9823292055099485, 'recall': 0.9871364653243848, 'f1': 0.9847269684078387, 'number': 7152} | {'precision': 0.6643835616438356, 'recall': 0.9238095238095239, 'f1': 0.7729083665338645, 'number': 105} | {'precision': 0.9248795080604952, 'recall': 0.9856535600425079, 'f1': 0.9542999228328902, 'number': 5646} | 0.8370 | 0.8772 | 0.8566 | 0.8285 |
73
+ | 2.3349 | 2.97 | 15000 | 2.3904 | {'precision': 0.6696704428424305, 'recall': 0.7589728625620076, 'f1': 0.7115305703734099, 'number': 6854} | {'precision': 0.8133933595948227, 'recall': 0.8170717919728661, 'f1': 0.8152284263959392, 'number': 8845} | {'precision': 0.9831593597773138, 'recall': 0.9876957494407159, 'f1': 0.9854223338215806, 'number': 7152} | {'precision': 0.60625, 'recall': 0.9238095238095239, 'f1': 0.7320754716981133, 'number': 105} | {'precision': 0.9244938599402589, 'recall': 0.9867162592986185, 'f1': 0.954592186429061, 'number': 5646} | 0.8380 | 0.8797 | 0.8584 | 0.8285 |
74
+ | 2.253 | 3.17 | 16000 | 2.3771 | {'precision': 0.669751896130608, 'recall': 0.7601400641960899, 'f1': 0.7120891136472357, 'number': 6854} | {'precision': 0.8152112676056338, 'recall': 0.817976257772753, 'f1': 0.8165914221218961, 'number': 8845} | {'precision': 0.9830130882762461, 'recall': 0.9871364653243848, 'f1': 0.9850704618389843, 'number': 7152} | {'precision': 0.64, 'recall': 0.9142857142857143, 'f1': 0.7529411764705883, 'number': 105} | {'precision': 0.924098986879256, 'recall': 0.9854764434998229, 'f1': 0.9538013199622868, 'number': 5646} | 0.8386 | 0.8798 | 0.8587 | 0.8302 |
75
+ | 2.2137 | 3.37 | 17000 | 2.3782 | {'precision': 0.6819264355649642, 'recall': 0.7519696527575138, 'f1': 0.7152373022481265, 'number': 6854} | {'precision': 0.8160893602617624, 'recall': 0.8177501413227812, 'f1': 0.816918906708832, 'number': 8845} | {'precision': 0.9831523252575884, 'recall': 0.9872762863534675, 'f1': 0.9852099902330124, 'number': 7152} | {'precision': 0.6530612244897959, 'recall': 0.9142857142857143, 'f1': 0.7619047619047618, 'number': 105} | {'precision': 0.924126455906822, 'recall': 0.983705278072972, 'f1': 0.9529855868222373, 'number': 5646} | 0.8433 | 0.8775 | 0.8601 | 0.8285 |
76
+ | 2.2065 | 3.56 | 18000 | 2.3393 | {'precision': 0.6767768810205675, 'recall': 0.7585351619492268, 'f1': 0.715327462850853, 'number': 6854} | {'precision': 0.8098028169014084, 'recall': 0.8125494629734313, 'f1': 0.8111738148984199, 'number': 8845} | {'precision': 0.9834238751915308, 'recall': 0.9871364653243848, 'f1': 0.9852766729467587, 'number': 7152} | {'precision': 0.6339869281045751, 'recall': 0.9238095238095239, 'f1': 0.751937984496124, 'number': 105} | {'precision': 0.9250207813798836, 'recall': 0.9854764434998229, 'f1': 0.9542920847268673, 'number': 5646} | 0.8396 | 0.8778 | 0.8583 | 0.8292 |
77
+ | 2.1758 | 3.76 | 19000 | 2.3063 | {'precision': 0.6791402304803833, 'recall': 0.7652465713451999, 'f1': 0.7196268093572066, 'number': 6854} | {'precision': 0.8155394707079846, 'recall': 0.8152628603730921, 'f1': 0.8154011420817548, 'number': 8845} | {'precision': 0.9828762355561743, 'recall': 0.9871364653243848, 'f1': 0.9850017439832579, 'number': 7152} | {'precision': 0.6510067114093959, 'recall': 0.9238095238095239, 'f1': 0.7637795275590552, 'number': 105} | {'precision': 0.9250457038391224, 'recall': 0.9858306765851931, 'f1': 0.9544714052988081, 'number': 5646} | 0.8417 | 0.8803 | 0.8606 | 0.8277 |
78
+ | 2.1417 | 3.96 | 20000 | 2.2882 | {'precision': 0.6788990825688074, 'recall': 0.7557630580682813, 'f1': 0.7152720243026789, 'number': 6854} | {'precision': 0.8162664250113276, 'recall': 0.8146975692481628, 'f1': 0.815481242573417, 'number': 8845} | {'precision': 0.9828905271943247, 'recall': 0.9879753914988815, 'f1': 0.9854263998326477, 'number': 7152} | {'precision': 0.6764705882352942, 'recall': 0.8761904761904762, 'f1': 0.7634854771784232, 'number': 105} | {'precision': 0.9258888332498748, 'recall': 0.9824654622741764, 'f1': 0.9533384893013664, 'number': 5646} | 0.8427 | 0.8772 | 0.8596 | 0.8285 |
79
+ | 2.0271 | 4.16 | 21000 | 2.3500 | {'precision': 0.6681376875551632, 'recall': 0.7731251823752553, 'f1': 0.7168075752451809, 'number': 6854} | {'precision': 0.815427927927928, 'recall': 0.8186546071226681, 'f1': 0.8170380818053596, 'number': 8845} | {'precision': 0.9826364772885123, 'recall': 0.9890939597315436, 'f1': 0.9858546442756603, 'number': 7152} | {'precision': 0.6838235294117647, 'recall': 0.8857142857142857, 'f1': 0.7717842323651452, 'number': 105} | {'precision': 0.922211188348229, 'recall': 0.9868933758413035, 'f1': 0.9534565366187543, 'number': 5646} | 0.8374 | 0.8838 | 0.8600 | 0.8299 |
80
+ | 2.0488 | 4.36 | 22000 | 2.2780 | {'precision': 0.6802249542244311, 'recall': 0.7588269623577473, 'f1': 0.7173793103448276, 'number': 6854} | {'precision': 0.8116153673331835, 'recall': 0.8168456755228943, 'f1': 0.814222122048797, 'number': 8845} | {'precision': 0.9827562230565985, 'recall': 0.9881152125279642, 'f1': 0.9854284319877291, 'number': 7152} | {'precision': 0.6533333333333333, 'recall': 0.9333333333333333, 'f1': 0.7686274509803921, 'number': 105} | {'precision': 0.9221338634857521, 'recall': 0.9858306765851931, 'f1': 0.9529190207156308, 'number': 5646} | 0.8407 | 0.8796 | 0.8597 | 0.8274 |
81
+ | 2.0403 | 4.55 | 23000 | 2.2557 | {'precision': 0.6836534692277538, 'recall': 0.7633498686898161, 'f1': 0.7213069552629764, 'number': 6854} | {'precision': 0.8174522436984288, 'recall': 0.8176370830977954, 'f1': 0.8175446529504862, 'number': 8845} | {'precision': 0.9833078314090973, 'recall': 0.9883948545861297, 'f1': 0.9858447806986962, 'number': 7152} | {'precision': 0.6906474820143885, 'recall': 0.9142857142857143, 'f1': 0.7868852459016393, 'number': 105} | {'precision': 0.9234465617232809, 'recall': 0.9870704923839887, 'f1': 0.9541991267870901, 'number': 5646} | 0.8439 | 0.8811 | 0.8621 | 0.8292 |
82
+ | 2.0443 | 4.75 | 24000 | 2.2284 | {'precision': 0.6855197695731867, 'recall': 0.7639334695068573, 'f1': 0.7226055754899255, 'number': 6854} | {'precision': 0.8167628096369189, 'recall': 0.8163934426229508, 'f1': 0.8165780843605112, 'number': 8845} | {'precision': 0.9827490261547023, 'recall': 0.9876957494407159, 'f1': 0.9852161785216179, 'number': 7152} | {'precision': 0.6830985915492958, 'recall': 0.9238095238095239, 'f1': 0.7854251012145749, 'number': 105} | {'precision': 0.9236641221374046, 'recall': 0.9858306765851931, 'f1': 0.9537354352296092, 'number': 5646} | 0.8441 | 0.8805 | 0.8619 | 0.8291 |
83
+ | 2.0214 | 4.95 | 25000 | 2.2037 | {'precision': 0.6887829426566018, 'recall': 0.7588269623577473, 'f1': 0.7221103783408538, 'number': 6854} | {'precision': 0.8133890268683676, 'recall': 0.814584511023177, 'f1': 0.8139863300005649, 'number': 8845} | {'precision': 0.9837319243604005, 'recall': 0.9892337807606264, 'f1': 0.9864751812604574, 'number': 7152} | {'precision': 0.7288135593220338, 'recall': 0.819047619047619, 'f1': 0.7713004484304932, 'number': 105} | {'precision': 0.9258766827322586, 'recall': 0.9867162592986185, 'f1': 0.9553288176283975, 'number': 5646} | 0.8454 | 0.8789 | 0.8618 | 0.8304 |
84
+ | 2.0081 | 5.15 | 26000 | 2.2014 | {'precision': 0.6996417745935519, 'recall': 0.7408812372337321, 'f1': 0.719671201814059, 'number': 6854} | {'precision': 0.8101595203077271, 'recall': 0.8096099491237988, 'f1': 0.8098846414838272, 'number': 8845} | {'precision': 0.9831851028349082, 'recall': 0.9892337807606264, 'f1': 0.9862001672706997, 'number': 7152} | {'precision': 0.6928571428571428, 'recall': 0.9238095238095239, 'f1': 0.7918367346938776, 'number': 105} | {'precision': 0.927212020033389, 'recall': 0.983705278072972, 'f1': 0.9546235819869371, 'number': 5646} | 0.8485 | 0.8728 | 0.8605 | 0.8273 |
85
+ | 1.9138 | 5.35 | 27000 | 2.1839 | {'precision': 0.6819591625743086, 'recall': 0.7699153778815291, 'f1': 0.7232730263157895, 'number': 6854} | {'precision': 0.8163679404802164, 'recall': 0.818767665347654, 'f1': 0.8175660419959357, 'number': 8845} | {'precision': 0.9829142936518961, 'recall': 0.9893736017897091, 'f1': 0.9861333704968295, 'number': 7152} | {'precision': 0.6893939393939394, 'recall': 0.8666666666666667, 'f1': 0.7679324894514767, 'number': 105} | {'precision': 0.9279731993299832, 'recall': 0.9812256464753808, 'f1': 0.9538567493112948, 'number': 5646} | 0.8434 | 0.8820 | 0.8623 | 0.8323 |
86
+ | 1.9304 | 5.54 | 28000 | 2.1557 | {'precision': 0.6910645118204889, 'recall': 0.7548876568427196, 'f1': 0.7215675336447948, 'number': 6854} | {'precision': 0.8137610519156654, 'recall': 0.8116449971735443, 'f1': 0.8127016471387332, 'number': 8845} | {'precision': 0.9831710709318497, 'recall': 0.9883948545861297, 'f1': 0.9857760423929716, 'number': 7152} | {'precision': 0.6689655172413793, 'recall': 0.9238095238095239, 'f1': 0.776, 'number': 105} | {'precision': 0.9272696873432537, 'recall': 0.9822883457314914, 'f1': 0.9539864109400533, 'number': 5646} | 0.8461 | 0.8763 | 0.8609 | 0.8287 |
87
+ | 1.9369 | 5.74 | 29000 | 2.1522 | {'precision': 0.6931558424095737, 'recall': 0.7521155529617741, 'f1': 0.7214330697641872, 'number': 6854} | {'precision': 0.8135497049477984, 'recall': 0.8105144149236857, 'f1': 0.8120292235374073, 'number': 8845} | {'precision': 0.9830508474576272, 'recall': 0.9893736017897091, 'f1': 0.9862020905923344, 'number': 7152} | {'precision': 0.7295081967213115, 'recall': 0.8476190476190476, 'f1': 0.7841409691629957, 'number': 105} | {'precision': 0.923140770252324, 'recall': 0.9849450938717677, 'f1': 0.9530419880034275, 'number': 5646} | 0.8465 | 0.8758 | 0.8609 | 0.8287 |
88
+ | 1.8944 | 5.94 | 30000 | 2.1284 | {'precision': 0.6882569773565034, 'recall': 0.762766267872775, 'f1': 0.723598615916955, 'number': 6854} | {'precision': 0.8153168417485598, 'recall': 0.8160542679479932, 'f1': 0.8156853881794554, 'number': 8845} | {'precision': 0.9816946331992789, 'recall': 0.9897930648769575, 'f1': 0.9857272157627236, 'number': 7152} | {'precision': 0.7073170731707317, 'recall': 0.8285714285714286, 'f1': 0.7631578947368421, 'number': 105} | {'precision': 0.9254028908456554, 'recall': 0.9865391427559334, 'f1': 0.9549935705100728, 'number': 5646} | 0.8450 | 0.8804 | 0.8623 | 0.8317 |
89
+ | 1.8311 | 6.14 | 31000 | 2.1711 | {'precision': 0.6781623822855688, 'recall': 0.7775021885030639, 'f1': 0.7244426318651441, 'number': 6854} | {'precision': 0.8175774647887324, 'recall': 0.8203504804974562, 'f1': 0.818961625282167, 'number': 8845} | {'precision': 0.9826292384658143, 'recall': 0.9886744966442953, 'f1': 0.9856425982715361, 'number': 7152} | {'precision': 0.71875, 'recall': 0.8761904761904762, 'f1': 0.7896995708154506, 'number': 105} | {'precision': 0.9265734265734266, 'recall': 0.9856535600425079, 'f1': 0.9552008238928938, 'number': 5646} | 0.8420 | 0.8850 | 0.8630 | 0.8315 |
90
+ | 1.879 | 6.34 | 32000 | 2.1473 | {'precision': 0.6905675353882789, 'recall': 0.7615990662386928, 'f1': 0.7243460764587525, 'number': 6854} | {'precision': 0.8152087812606088, 'recall': 0.8144714527981911, 'f1': 0.8148399502318742, 'number': 8845} | {'precision': 0.9807692307692307, 'recall': 0.9911912751677853, 'f1': 0.985952712100139, 'number': 7152} | {'precision': 0.7022900763358778, 'recall': 0.8761904761904762, 'f1': 0.7796610169491526, 'number': 105} | {'precision': 0.9232935719019219, 'recall': 0.9870704923839887, 'f1': 0.9541174456428694, 'number': 5646} | 0.8452 | 0.8803 | 0.8624 | 0.8306 |
91
+ | 1.8279 | 6.53 | 33000 | 2.1636 | {'precision': 0.6845568313765966, 'recall': 0.7741464838050773, 'f1': 0.7266004792879152, 'number': 6854} | {'precision': 0.8150022492127755, 'recall': 0.8193329564725834, 'f1': 0.8171618650279078, 'number': 8845} | {'precision': 0.9826340650180606, 'recall': 0.9889541387024608, 'f1': 0.9857839721254356, 'number': 7152} | {'precision': 0.7258064516129032, 'recall': 0.8571428571428571, 'f1': 0.7860262008733625, 'number': 105} | {'precision': 0.9263262930317645, 'recall': 0.9865391427559334, 'f1': 0.9554850330216998, 'number': 5646} | 0.8435 | 0.8841 | 0.8633 | 0.8314 |
92
+ | 1.8613 | 6.73 | 34000 | 2.1192 | {'precision': 0.6884180423761861, 'recall': 0.7726874817624745, 'f1': 0.7281226369698219, 'number': 6854} | {'precision': 0.8161166365280289, 'recall': 0.8163934426229508, 'f1': 0.8162550161080653, 'number': 8845} | {'precision': 0.9811529933481153, 'recall': 0.9899328859060402, 'f1': 0.9855233853006681, 'number': 7152} | {'precision': 0.6666666666666666, 'recall': 0.9333333333333333, 'f1': 0.7777777777777778, 'number': 105} | {'precision': 0.9258397073495178, 'recall': 0.9861849096705633, 'f1': 0.9550600343053174, 'number': 5646} | 0.8444 | 0.8833 | 0.8634 | 0.8334 |
93
+ | 1.8604 | 6.93 | 35000 | 2.1070 | {'precision': 0.68467659137577, 'recall': 0.7783775897286256, 'f1': 0.7285265601529427, 'number': 6854} | {'precision': 0.8169934640522876, 'recall': 0.819672131147541, 'f1': 0.8183306055646481, 'number': 8845} | {'precision': 0.9827945053420286, 'recall': 0.9903523489932886, 'f1': 0.9865589525732991, 'number': 7152} | {'precision': 0.6884057971014492, 'recall': 0.9047619047619048, 'f1': 0.7818930041152263, 'number': 105} | {'precision': 0.9267643142476698, 'recall': 0.9861849096705633, 'f1': 0.9555517418911963, 'number': 5646} | 0.8438 | 0.8856 | 0.8642 | 0.8343 |
94
+ | 1.8026 | 7.13 | 36000 | 2.1282 | {'precision': 0.695146409947854, 'recall': 0.7585351619492268, 'f1': 0.7254587315984092, 'number': 6854} | {'precision': 0.8139561185252205, 'recall': 0.81368004522329, 'f1': 0.8138180584610165, 'number': 8845} | {'precision': 0.9833194328607172, 'recall': 0.9890939597315436, 'f1': 0.9861982434127978, 'number': 7152} | {'precision': 0.6976744186046512, 'recall': 0.8571428571428571, 'f1': 0.7692307692307693, 'number': 105} | {'precision': 0.926808936312104, 'recall': 0.9845908607863975, 'f1': 0.9548265200961868, 'number': 5646} | 0.8474 | 0.8782 | 0.8625 | 0.8295 |
95
+ | 1.774 | 7.33 | 37000 | 2.1375 | {'precision': 0.6926958831341301, 'recall': 0.7610154654216515, 'f1': 0.7252502780867629, 'number': 6854} | {'precision': 0.8117753011370032, 'recall': 0.8152628603730921, 'f1': 0.8135153429602889, 'number': 8845} | {'precision': 0.9819669857123041, 'recall': 0.9897930648769575, 'f1': 0.9858644941160087, 'number': 7152} | {'precision': 0.7209302325581395, 'recall': 0.8857142857142857, 'f1': 0.7948717948717948, 'number': 105} | {'precision': 0.9258209701616936, 'recall': 0.983705278072972, 'f1': 0.953885787891799, 'number': 5646} | 0.8455 | 0.8794 | 0.8621 | 0.8300 |
96
+ | 1.8132 | 7.52 | 38000 | 2.1094 | {'precision': 0.6921750663129973, 'recall': 0.7614531660344325, 'f1': 0.7251632624704737, 'number': 6854} | {'precision': 0.8149196287072674, 'recall': 0.8139061616732617, 'f1': 0.8144125798970531, 'number': 8845} | {'precision': 0.9827825603998889, 'recall': 0.9896532438478747, 'f1': 0.9862059356276995, 'number': 7152} | {'precision': 0.7058823529411765, 'recall': 0.9142857142857143, 'f1': 0.7966804979253113, 'number': 105} | {'precision': 0.9252615844544095, 'recall': 0.9867162592986185, 'f1': 0.9550012856775519, 'number': 5646} | 0.8463 | 0.8798 | 0.8627 | 0.8299 |
97
+ | 1.805 | 7.72 | 39000 | 2.1104 | {'precision': 0.6876955161626694, 'recall': 0.7697694776772688, 'f1': 0.7264215888751205, 'number': 6854} | {'precision': 0.8163380920009065, 'recall': 0.814584511023177, 'f1': 0.815460358779922, 'number': 8845} | {'precision': 0.9823831321958663, 'recall': 0.9902125279642058, 'f1': 0.9862822923194763, 'number': 7152} | {'precision': 0.7165354330708661, 'recall': 0.8666666666666667, 'f1': 0.7844827586206896, 'number': 105} | {'precision': 0.9255442911750041, 'recall': 0.9863620262132483, 'f1': 0.9549858526965618, 'number': 5646} | 0.8450 | 0.8819 | 0.8630 | 0.8331 |
98
+ | 1.7337 | 7.92 | 40000 | 2.1034 | {'precision': 0.6904604829133131, 'recall': 0.7634957688940764, 'f1': 0.7251437677544517, 'number': 6854} | {'precision': 0.8152542372881356, 'recall': 0.8157150932730356, 'f1': 0.8154846001695395, 'number': 8845} | {'precision': 0.9833333333333333, 'recall': 0.9899328859060402, 'f1': 0.9866220735785953, 'number': 7152} | {'precision': 0.7, 'recall': 0.9333333333333333, 'f1': 0.8, 'number': 105} | {'precision': 0.9253284550141361, 'recall': 0.9854764434998229, 'f1': 0.9544557852302942, 'number': 5646} | 0.8458 | 0.8807 | 0.8629 | 0.8306 |
99
+ | 1.7771 | 8.12 | 41000 | 2.1074 | {'precision': 0.6949152542372882, 'recall': 0.759702363583309, 'f1': 0.7258660347110893, 'number': 6854} | {'precision': 0.8133830677065672, 'recall': 0.8135669869983041, 'f1': 0.8134750169568167, 'number': 8845} | {'precision': 0.9833240689271817, 'recall': 0.9893736017897091, 'f1': 0.9863395595204906, 'number': 7152} | {'precision': 0.7244094488188977, 'recall': 0.8761904761904762, 'f1': 0.7931034482758621, 'number': 105} | {'precision': 0.9278677575555184, 'recall': 0.9842366277010273, 'f1': 0.9552213149978513, 'number': 5646} | 0.8474 | 0.8785 | 0.8627 | 0.8286 |
100
+ | 1.7179 | 8.32 | 42000 | 2.1069 | {'precision': 0.6874355005159959, 'recall': 0.7775021885030639, 'f1': 0.7297001232370259, 'number': 6854} | {'precision': 0.8154802259887005, 'recall': 0.8159412097230073, 'f1': 0.8157106527267589, 'number': 8845} | {'precision': 0.982923781757601, 'recall': 0.9899328859060402, 'f1': 0.9864158829676071, 'number': 7152} | {'precision': 0.6971830985915493, 'recall': 0.9428571428571428, 'f1': 0.8016194331983806, 'number': 105} | {'precision': 0.9244437064098306, 'recall': 0.9860077931278781, 'f1': 0.954233801851217, 'number': 5646} | 0.8439 | 0.8843 | 0.8636 | 0.8319 |
101
+ | 1.7005 | 8.51 | 43000 | 2.1151 | {'precision': 0.694326052210975, 'recall': 0.7605777648088707, 'f1': 0.7259434619133825, 'number': 6854} | {'precision': 0.8143164084586678, 'recall': 0.8141322781232334, 'f1': 0.8142243328810492, 'number': 8845} | {'precision': 0.9827873403664631, 'recall': 0.9899328859060402, 'f1': 0.9863471719141822, 'number': 7152} | {'precision': 0.7317073170731707, 'recall': 0.8571428571428571, 'f1': 0.7894736842105263, 'number': 105} | {'precision': 0.9230514096185738, 'recall': 0.9858306765851931, 'f1': 0.9534087016101404, 'number': 5646} | 0.8466 | 0.8793 | 0.8626 | 0.8293 |
102
+ | 1.7078 | 8.71 | 44000 | 2.1110 | {'precision': 0.6905515967273687, 'recall': 0.7634957688940764, 'f1': 0.7251940133037693, 'number': 6854} | {'precision': 0.8151706986208456, 'recall': 0.8152628603730921, 'f1': 0.8152167768922051, 'number': 8845} | {'precision': 0.9834653327775462, 'recall': 0.9896532438478747, 'f1': 0.9865495853369572, 'number': 7152} | {'precision': 0.706766917293233, 'recall': 0.8952380952380953, 'f1': 0.7899159663865547, 'number': 105} | {'precision': 0.9254152823920265, 'recall': 0.9867162592986185, 'f1': 0.9550831476084348, 'number': 5646} | 0.8459 | 0.8806 | 0.8629 | 0.8313 |
103
+ | 1.7494 | 8.91 | 45000 | 2.1095 | {'precision': 0.6886890800104248, 'recall': 0.7710825795156113, 'f1': 0.7275605726872247, 'number': 6854} | {'precision': 0.8156557099288377, 'recall': 0.8163934426229508, 'f1': 0.8160244095378009, 'number': 8845} | {'precision': 0.9830626128002221, 'recall': 0.9900727069351231, 'f1': 0.9865552072448623, 'number': 7152} | {'precision': 0.706766917293233, 'recall': 0.8952380952380953, 'f1': 0.7899159663865547, 'number': 105} | {'precision': 0.924506387921022, 'recall': 0.9868933758413035, 'f1': 0.9546817441960078, 'number': 5646} | 0.8449 | 0.8829 | 0.8635 | 0.8319 |
104
+ | 1.6805 | 9.11 | 46000 | 2.1132 | {'precision': 0.6890920966688439, 'recall': 0.7696235774730085, 'f1': 0.727134881797505, 'number': 6854} | {'precision': 0.8149027589326097, 'recall': 0.8148106274731487, 'f1': 0.8148566905986773, 'number': 8845} | {'precision': 0.9830673143650243, 'recall': 0.9903523489932886, 'f1': 0.9866963850386571, 'number': 7152} | {'precision': 0.697841726618705, 'recall': 0.9238095238095239, 'f1': 0.7950819672131149, 'number': 105} | {'precision': 0.9251745926172265, 'recall': 0.9854764434998229, 'f1': 0.9543739279588336, 'number': 5646} | 0.8449 | 0.8820 | 0.8630 | 0.8327 |
105
+ | 1.6867 | 9.31 | 47000 | 2.1126 | {'precision': 0.6902941557600104, 'recall': 0.7772103880945433, 'f1': 0.7311783679912154, 'number': 6854} | {'precision': 0.8172370947701344, 'recall': 0.817976257772753, 'f1': 0.8176065092100803, 'number': 8845} | {'precision': 0.9831967782252465, 'recall': 0.9899328859060402, 'f1': 0.9865533337978123, 'number': 7152} | {'precision': 0.7121212121212122, 'recall': 0.8952380952380953, 'f1': 0.7932489451476793, 'number': 105} | {'precision': 0.925058158856763, 'recall': 0.9860077931278781, 'f1': 0.9545610425240054, 'number': 5646} | 0.8457 | 0.8847 | 0.8647 | 0.8326 |
106
+ | 1.7212 | 9.5 | 48000 | 2.1058 | {'precision': 0.6885822158573103, 'recall': 0.7716661803326524, 'f1': 0.7277605779153767, 'number': 6854} | {'precision': 0.8145762711864407, 'recall': 0.8150367439231204, 'f1': 0.8148064424978807, 'number': 8845} | {'precision': 0.98319211001528, 'recall': 0.9896532438478747, 'f1': 0.9864120967179988, 'number': 7152} | {'precision': 0.6956521739130435, 'recall': 0.9142857142857143, 'f1': 0.7901234567901234, 'number': 105} | {'precision': 0.9243404678944749, 'recall': 0.9867162592986185, 'f1': 0.9545104086353122, 'number': 5646} | 0.8444 | 0.8826 | 0.8631 | 0.8319 |
107
+ | 1.6952 | 9.7 | 49000 | 2.1104 | {'precision': 0.6893522161028062, 'recall': 0.7669973737963233, 'f1': 0.7261049723756906, 'number': 6854} | {'precision': 0.8150282485875706, 'recall': 0.8154889768230639, 'f1': 0.81525854761232, 'number': 8845} | {'precision': 0.9829308909242298, 'recall': 0.9903523489932886, 'f1': 0.9866276640200585, 'number': 7152} | {'precision': 0.7037037037037037, 'recall': 0.9047619047619048, 'f1': 0.7916666666666667, 'number': 105} | {'precision': 0.9249044691809271, 'recall': 0.9860077931278781, 'f1': 0.9544792113159023, 'number': 5646} | 0.8451 | 0.8816 | 0.8630 | 0.8311 |
108
+ | 1.7128 | 9.9 | 50000 | 2.1040 | {'precision': 0.6902458158995816, 'recall': 0.7702071782900496, 'f1': 0.7280375120673009, 'number': 6854} | {'precision': 0.8152542372881356, 'recall': 0.8157150932730356, 'f1': 0.8154846001695395, 'number': 8845} | {'precision': 0.9829308909242298, 'recall': 0.9903523489932886, 'f1': 0.9866276640200585, 'number': 7152} | {'precision': 0.6934306569343066, 'recall': 0.9047619047619048, 'f1': 0.7851239669421487, 'number': 105} | {'precision': 0.9253532834580216, 'recall': 0.9858306765851931, 'f1': 0.9546351084812623, 'number': 5646} | 0.8453 | 0.8824 | 0.8635 | 0.8311 |
109
 
110
 
111
  ### Framework versions
all_results.json CHANGED
@@ -1,41 +1,41 @@
1
  {
2
- "epoch": 3.0,
3
  "eval_COMMENT": {
4
- "f1": 0.7115079365079365,
5
- "number": 7098,
6
- "precision": 0.6705310396409873,
7
- "recall": 0.7578191039729502
8
  },
9
  "eval_NAME": {
10
- "f1": 0.8179719791722584,
11
- "number": 9281,
12
- "precision": 0.8150406504065041,
13
- "recall": 0.8209244693459756
14
  },
15
  "eval_QTY": {
16
- "f1": 0.9859043081199126,
17
- "number": 7557,
18
- "precision": 0.9861000794281175,
19
- "recall": 0.9857086145295753
20
  },
21
  "eval_RANGE_END": {
22
- "f1": 0.7338709677419355,
23
- "number": 96,
24
- "precision": 0.5986842105263158,
25
- "recall": 0.9479166666666666
26
  },
27
  "eval_UNIT": {
28
- "f1": 0.9530911715179216,
29
- "number": 6029,
30
- "precision": 0.9225395839801304,
31
- "recall": 0.985735611212473
32
  },
33
- "eval_loss": 2.572307586669922,
34
- "eval_overall_accuracy": 0.8329675956404067,
35
- "eval_overall_f1": 0.8600659315675797,
36
- "eval_overall_precision": 0.8401865600609175,
37
- "eval_overall_recall": 0.8809088187352383,
38
- "eval_runtime": 10.0829,
39
- "eval_samples_per_second": 888.036,
40
- "eval_steps_per_second": 27.77
41
  }
 
1
  {
2
+ "epoch": 10.0,
3
  "eval_COMMENT": {
4
+ "f1": 0.7340833884844474,
5
+ "number": 7201,
6
+ "precision": 0.7012264508787457,
7
+ "recall": 0.7701708096097765
8
  },
9
  "eval_NAME": {
10
+ "f1": 0.8171800247271946,
11
+ "number": 9275,
12
+ "precision": 0.8148584905660378,
13
+ "recall": 0.8195148247978437
14
  },
15
  "eval_QTY": {
16
+ "f1": 0.9862192929898143,
17
+ "number": 7496,
18
+ "precision": 0.9843189368770764,
19
+ "recall": 0.9881270010672358
20
  },
21
  "eval_RANGE_END": {
22
+ "f1": 0.7662835249042146,
23
+ "number": 108,
24
+ "precision": 0.6535947712418301,
25
+ "recall": 0.9259259259259259
26
  },
27
  "eval_UNIT": {
28
+ "f1": 0.9568287594286632,
29
+ "number": 6050,
30
+ "precision": 0.9298190892077355,
31
+ "recall": 0.9854545454545455
32
  },
33
+ "eval_loss": 2.074584484100342,
34
+ "eval_overall_accuracy": 0.8371684620258893,
35
+ "eval_overall_f1": 0.8661665880208926,
36
+ "eval_overall_precision": 0.8496185399176429,
37
+ "eval_overall_recall": 0.8833720544307999,
38
+ "eval_runtime": 10.6256,
39
+ "eval_samples_per_second": 842.685,
40
+ "eval_steps_per_second": 26.352
41
  }
pytorch_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:4fe51036b0fe145c1633527037e9fd147f46ac6333b510111d93b14646958829
3
  size 69005087
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:08869ab966aebcc371993ea45597c2f2c74a93124b977448d2ccac4e0c9dda86
3
  size 69005087
test_results.json CHANGED
@@ -1,41 +1,41 @@
1
  {
2
- "epoch": 3.0,
3
  "eval_COMMENT": {
4
- "f1": 0.7115079365079365,
5
- "number": 7098,
6
- "precision": 0.6705310396409873,
7
- "recall": 0.7578191039729502
8
  },
9
  "eval_NAME": {
10
- "f1": 0.8179719791722584,
11
- "number": 9281,
12
- "precision": 0.8150406504065041,
13
- "recall": 0.8209244693459756
14
  },
15
  "eval_QTY": {
16
- "f1": 0.9859043081199126,
17
- "number": 7557,
18
- "precision": 0.9861000794281175,
19
- "recall": 0.9857086145295753
20
  },
21
  "eval_RANGE_END": {
22
- "f1": 0.7338709677419355,
23
- "number": 96,
24
- "precision": 0.5986842105263158,
25
- "recall": 0.9479166666666666
26
  },
27
  "eval_UNIT": {
28
- "f1": 0.9530911715179216,
29
- "number": 6029,
30
- "precision": 0.9225395839801304,
31
- "recall": 0.985735611212473
32
  },
33
- "eval_loss": 2.572307586669922,
34
- "eval_overall_accuracy": 0.8329675956404067,
35
- "eval_overall_f1": 0.8600659315675797,
36
- "eval_overall_precision": 0.8401865600609175,
37
- "eval_overall_recall": 0.8809088187352383,
38
- "eval_runtime": 10.0829,
39
- "eval_samples_per_second": 888.036,
40
- "eval_steps_per_second": 27.77
41
  }
 
1
  {
2
+ "epoch": 10.0,
3
  "eval_COMMENT": {
4
+ "f1": 0.7340833884844474,
5
+ "number": 7201,
6
+ "precision": 0.7012264508787457,
7
+ "recall": 0.7701708096097765
8
  },
9
  "eval_NAME": {
10
+ "f1": 0.8171800247271946,
11
+ "number": 9275,
12
+ "precision": 0.8148584905660378,
13
+ "recall": 0.8195148247978437
14
  },
15
  "eval_QTY": {
16
+ "f1": 0.9862192929898143,
17
+ "number": 7496,
18
+ "precision": 0.9843189368770764,
19
+ "recall": 0.9881270010672358
20
  },
21
  "eval_RANGE_END": {
22
+ "f1": 0.7662835249042146,
23
+ "number": 108,
24
+ "precision": 0.6535947712418301,
25
+ "recall": 0.9259259259259259
26
  },
27
  "eval_UNIT": {
28
+ "f1": 0.9568287594286632,
29
+ "number": 6050,
30
+ "precision": 0.9298190892077355,
31
+ "recall": 0.9854545454545455
32
  },
33
+ "eval_loss": 2.074584484100342,
34
+ "eval_overall_accuracy": 0.8371684620258893,
35
+ "eval_overall_f1": 0.8661665880208926,
36
+ "eval_overall_precision": 0.8496185399176429,
37
+ "eval_overall_recall": 0.8833720544307999,
38
+ "eval_runtime": 10.6256,
39
+ "eval_samples_per_second": 842.685,
40
+ "eval_steps_per_second": 26.352
41
  }
train_results.json CHANGED
@@ -1,41 +1,41 @@
1
  {
2
- "epoch": 3.0,
3
  "eval_COMMENT": {
4
- "f1": 0.721799355413838,
5
- "number": 129768,
6
- "precision": 0.6788247832786863,
7
- "recall": 0.7705828863818507
8
  },
9
  "eval_NAME": {
10
- "f1": 0.8235496724923245,
11
- "number": 167686,
12
- "precision": 0.8201064458900059,
13
- "recall": 0.8270219338525577
14
  },
15
  "eval_QTY": {
16
- "f1": 0.984932056268375,
17
- "number": 135815,
18
- "precision": 0.9844285567177133,
19
- "recall": 0.9854360711261643
20
  },
21
  "eval_RANGE_END": {
22
- "f1": 0.7352039613298751,
23
- "number": 1680,
24
- "precision": 0.6087465833658727,
25
- "recall": 0.9279761904761905
26
  },
27
  "eval_UNIT": {
28
- "f1": 0.9542982760615527,
29
- "number": 108817,
30
- "precision": 0.9251343819294052,
31
- "recall": 0.9853607432662176
32
  },
33
- "eval_loss": 2.4726200103759766,
34
- "eval_overall_accuracy": 0.8400964270928377,
35
- "eval_overall_f1": 0.8636297978361569,
36
- "eval_overall_precision": 0.8431603381071257,
37
- "eval_overall_recall": 0.8851178631985082,
38
- "eval_runtime": 178.5371,
39
- "eval_samples_per_second": 905.151,
40
- "eval_steps_per_second": 28.291
41
  }
 
1
  {
2
+ "epoch": 10.0,
3
  "eval_COMMENT": {
4
+ "f1": 0.7828024124108719,
5
+ "number": 129733,
6
+ "precision": 0.7460209932327204,
7
+ "recall": 0.8233988268212405
8
  },
9
  "eval_NAME": {
10
+ "f1": 0.843375288153968,
11
+ "number": 167680,
12
+ "precision": 0.842376753650091,
13
+ "recall": 0.8443761927480916
14
  },
15
  "eval_QTY": {
16
+ "f1": 0.9885295728267381,
17
+ "number": 135816,
18
+ "precision": 0.9868647954503761,
19
+ "recall": 0.9901999764387112
20
  },
21
  "eval_RANGE_END": {
22
+ "f1": 0.7818455366098295,
23
+ "number": 1651,
24
+ "precision": 0.6670945656824989,
25
+ "recall": 0.9442761962447002
26
  },
27
  "eval_UNIT": {
28
+ "f1": 0.958128584041595,
29
+ "number": 108857,
30
+ "precision": 0.9309624699959272,
31
+ "recall": 0.9869278043671973
32
  },
33
+ "eval_loss": 1.6188573837280273,
34
+ "eval_overall_accuracy": 0.8681037030187413,
35
+ "eval_overall_f1": 0.8870648511249151,
36
+ "eval_overall_precision": 0.8701616897820549,
37
+ "eval_overall_recall": 0.904637720074227,
38
+ "eval_runtime": 181.658,
39
+ "eval_samples_per_second": 889.6,
40
+ "eval_steps_per_second": 27.805
41
  }
trainer_state.json CHANGED
@@ -1,838 +1,2734 @@
1
  {
2
- "best_metric": null,
3
- "best_model_checkpoint": null,
4
- "epoch": 3.0,
5
  "eval_steps": 1000,
6
- "global_step": 15153,
7
  "is_hyper_param_search": false,
8
  "is_local_process_zero": true,
9
  "is_world_process_zero": true,
10
  "log_history": [
11
  {
12
  "epoch": 0.1,
13
- "learning_rate": 4.835016168415495e-05,
14
- "loss": 6.7872,
15
  "step": 500
16
  },
17
  {
18
  "epoch": 0.2,
19
- "learning_rate": 4.670032336830991e-05,
20
- "loss": 4.174,
21
  "step": 1000
22
  },
23
  {
24
  "epoch": 0.2,
25
  "eval_COMMENT": {
26
- "f1": 0.5753388429752067,
27
- "number": 6922,
28
- "precision": 0.5304157015725954,
29
- "recall": 0.6285755561976307
30
  },
31
  "eval_NAME": {
32
- "f1": 0.7866681381745945,
33
- "number": 8833,
34
- "precision": 0.7673592421143288,
35
- "recall": 0.8069738480697385
36
  },
37
  "eval_QTY": {
38
- "f1": 0.9736805263894722,
39
- "number": 7092,
40
- "precision": 0.9667778704475952,
41
- "recall": 0.9806824591088551
42
  },
43
  "eval_RANGE_END": {
44
  "f1": 0.0,
45
- "number": 88,
46
  "precision": 0.0,
47
  "recall": 0.0
48
  },
49
  "eval_UNIT": {
50
- "f1": 0.9428498856997714,
51
- "number": 5707,
52
- "precision": 0.9121887287024901,
53
- "recall": 0.9756439460311898
54
- },
55
- "eval_loss": 3.8689863681793213,
56
- "eval_overall_accuracy": 0.7961931378288045,
57
- "eval_overall_f1": 0.8077130165567371,
58
- "eval_overall_precision": 0.7795388113023709,
59
- "eval_overall_recall": 0.838000139655052,
60
- "eval_runtime": 10.0032,
61
- "eval_samples_per_second": 850.33,
62
- "eval_steps_per_second": 26.592,
63
  "step": 1000
64
  },
65
  {
66
  "epoch": 0.3,
67
- "learning_rate": 4.505048505246486e-05,
68
- "loss": 3.6785,
69
  "step": 1500
70
  },
71
  {
72
  "epoch": 0.4,
73
- "learning_rate": 4.3400646736619816e-05,
74
- "loss": 3.5528,
75
  "step": 2000
76
  },
77
  {
78
  "epoch": 0.4,
79
  "eval_COMMENT": {
80
- "f1": 0.6020648196549921,
81
- "number": 6922,
82
- "precision": 0.5496301598663803,
83
- "recall": 0.6655590869690841
84
  },
85
  "eval_NAME": {
86
- "f1": 0.7944308852895496,
87
- "number": 8833,
88
- "precision": 0.7787928221859707,
89
- "recall": 0.8107098381070984
90
  },
91
  "eval_QTY": {
92
- "f1": 0.9785673998871969,
93
- "number": 7092,
94
- "precision": 0.9785673998871969,
95
- "recall": 0.9785673998871969
96
  },
97
  "eval_RANGE_END": {
98
- "f1": 0.22641509433962262,
99
- "number": 88,
100
- "precision": 0.6666666666666666,
101
- "recall": 0.13636363636363635
102
- },
103
- "eval_UNIT": {
104
- "f1": 0.9445616403679015,
105
- "number": 5707,
106
- "precision": 0.9109700520833334,
107
- "recall": 0.9807254249167688
108
- },
109
- "eval_loss": 3.415388822555542,
110
- "eval_overall_accuracy": 0.8041807504201522,
111
- "eval_overall_f1": 0.8177492307433626,
112
- "eval_overall_precision": 0.788719146313775,
113
- "eval_overall_recall": 0.8489979750017457,
114
- "eval_runtime": 10.2481,
115
- "eval_samples_per_second": 830.011,
116
- "eval_steps_per_second": 25.956,
117
  "step": 2000
118
  },
119
  {
120
  "epoch": 0.49,
121
- "learning_rate": 4.1750808420774766e-05,
122
- "loss": 3.3872,
123
  "step": 2500
124
  },
125
  {
126
  "epoch": 0.59,
127
- "learning_rate": 4.010097010492972e-05,
128
- "loss": 3.3333,
129
  "step": 3000
130
  },
131
  {
132
  "epoch": 0.59,
133
  "eval_COMMENT": {
134
- "f1": 0.6369560924231453,
135
- "number": 6922,
136
- "precision": 0.5850767928407304,
137
- "recall": 0.6989309448136377
138
  },
139
  "eval_NAME": {
140
- "f1": 0.7949638301397095,
141
- "number": 8833,
142
- "precision": 0.7759810263044415,
143
- "recall": 0.814898675421714
144
  },
145
  "eval_QTY": {
146
- "f1": 0.9801268498942918,
147
- "number": 7092,
148
- "precision": 0.9797125950972105,
149
- "recall": 0.9805414551607445
150
  },
151
  "eval_RANGE_END": {
152
- "f1": 0.6666666666666667,
153
- "number": 88,
154
- "precision": 0.6867469879518072,
155
- "recall": 0.6477272727272727
156
  },
157
  "eval_UNIT": {
158
- "f1": 0.948932536293766,
159
- "number": 5707,
160
- "precision": 0.9255372313843079,
161
- "recall": 0.9735412651130191
162
- },
163
- "eval_loss": 3.1915245056152344,
164
- "eval_overall_accuracy": 0.8124138451951584,
165
- "eval_overall_f1": 0.8287884657492717,
166
- "eval_overall_precision": 0.8006443424777897,
167
- "eval_overall_recall": 0.8589833112212835,
168
- "eval_runtime": 11.2414,
169
- "eval_samples_per_second": 756.666,
170
- "eval_steps_per_second": 23.662,
171
  "step": 3000
172
  },
173
  {
174
  "epoch": 0.69,
175
- "learning_rate": 3.845113178908467e-05,
176
- "loss": 3.2244,
177
  "step": 3500
178
  },
179
  {
180
  "epoch": 0.79,
181
- "learning_rate": 3.680129347323962e-05,
182
- "loss": 3.1122,
183
  "step": 4000
184
  },
185
  {
186
  "epoch": 0.79,
187
  "eval_COMMENT": {
188
- "f1": 0.6578412740022282,
189
- "number": 6922,
190
- "precision": 0.6020151133501259,
191
- "recall": 0.7250794568043918
192
  },
193
  "eval_NAME": {
194
- "f1": 0.8043938887030222,
195
- "number": 8833,
196
- "precision": 0.7925502692011867,
197
- "recall": 0.8165968527114231
198
  },
199
  "eval_QTY": {
200
- "f1": 0.9807353044950956,
201
- "number": 7092,
202
- "precision": 0.9816358242689646,
203
- "recall": 0.9798364354201917
204
  },
205
  "eval_RANGE_END": {
206
- "f1": 0.6755555555555556,
207
- "number": 88,
208
- "precision": 0.5547445255474452,
209
- "recall": 0.8636363636363636
210
  },
211
  "eval_UNIT": {
212
- "f1": 0.9479572808950669,
213
- "number": 5707,
214
- "precision": 0.9180758496141849,
215
- "recall": 0.9798493078675311
216
- },
217
- "eval_loss": 3.055974245071411,
218
- "eval_overall_accuracy": 0.8183054176029609,
219
- "eval_overall_f1": 0.8368498156162123,
220
- "eval_overall_precision": 0.8082289803220036,
221
- "eval_overall_recall": 0.8675720969206061,
222
- "eval_runtime": 13.0303,
223
- "eval_samples_per_second": 652.785,
224
- "eval_steps_per_second": 20.414,
225
  "step": 4000
226
  },
227
  {
228
  "epoch": 0.89,
229
- "learning_rate": 3.515145515739457e-05,
230
- "loss": 3.0919,
231
  "step": 4500
232
  },
233
  {
234
  "epoch": 0.99,
235
- "learning_rate": 3.3501616841549535e-05,
236
- "loss": 3.074,
237
  "step": 5000
238
  },
239
  {
240
  "epoch": 0.99,
241
  "eval_COMMENT": {
242
- "f1": 0.6620227729403884,
243
- "number": 6922,
244
- "precision": 0.6171328671328671,
245
- "recall": 0.7139555041895406
246
  },
247
  "eval_NAME": {
248
- "f1": 0.8096975138896684,
249
- "number": 8833,
250
- "precision": 0.8028043623414199,
251
- "recall": 0.816710064530737
252
  },
253
  "eval_QTY": {
254
- "f1": 0.9794429242966393,
255
- "number": 7092,
256
- "precision": 0.9747242005306521,
257
- "recall": 0.9842075578116187
258
  },
259
  "eval_RANGE_END": {
260
- "f1": 0.7076923076923077,
261
- "number": 88,
262
- "precision": 0.6448598130841121,
263
- "recall": 0.7840909090909091
264
  },
265
  "eval_UNIT": {
266
- "f1": 0.9461453651089815,
267
- "number": 5707,
268
- "precision": 0.9168310322156475,
269
- "recall": 0.9773961801296653
270
- },
271
- "eval_loss": 2.949470043182373,
272
- "eval_overall_accuracy": 0.820892422153823,
273
- "eval_overall_f1": 0.840272597816505,
274
- "eval_overall_precision": 0.8166809464179793,
275
- "eval_overall_recall": 0.8652677885622513,
276
- "eval_runtime": 11.1611,
277
- "eval_samples_per_second": 762.109,
278
- "eval_steps_per_second": 23.833,
279
  "step": 5000
280
  },
281
  {
282
  "epoch": 1.09,
283
- "learning_rate": 3.1851778525704485e-05,
284
- "loss": 2.9268,
285
  "step": 5500
286
  },
287
  {
288
  "epoch": 1.19,
289
- "learning_rate": 3.0201940209859435e-05,
290
- "loss": 2.936,
291
  "step": 6000
292
  },
293
  {
294
  "epoch": 1.19,
295
  "eval_COMMENT": {
296
- "f1": 0.6634152949942423,
297
- "number": 6922,
298
- "precision": 0.6245376865195765,
299
- "recall": 0.7074544929211211
300
  },
301
  "eval_NAME": {
302
- "f1": 0.8093132590809874,
303
- "number": 8833,
304
- "precision": 0.8003099402258136,
305
- "recall": 0.81852145363976
306
  },
307
  "eval_QTY": {
308
- "f1": 0.9790689534476724,
309
- "number": 7092,
310
- "precision": 0.9721951897678298,
311
- "recall": 0.9860406091370558
312
  },
313
  "eval_RANGE_END": {
314
- "f1": 0.7348837209302326,
315
- "number": 88,
316
- "precision": 0.6220472440944882,
317
- "recall": 0.8977272727272727
318
  },
319
  "eval_UNIT": {
320
- "f1": 0.9469594594594595,
321
- "number": 5707,
322
- "precision": 0.9140714169248328,
323
- "recall": 0.9823024356053969
324
- },
325
- "eval_loss": 2.889272451400757,
326
- "eval_overall_accuracy": 0.8216855184394887,
327
- "eval_overall_f1": 0.8412752246905207,
328
- "eval_overall_precision": 0.8178910577683989,
329
- "eval_overall_recall": 0.8660358913483696,
330
- "eval_runtime": 12.795,
331
- "eval_samples_per_second": 664.793,
332
- "eval_steps_per_second": 20.789,
333
  "step": 6000
334
  },
335
  {
336
  "epoch": 1.29,
337
- "learning_rate": 2.855210189401439e-05,
338
- "loss": 2.8799,
339
  "step": 6500
340
  },
341
  {
342
  "epoch": 1.39,
343
- "learning_rate": 2.690226357816934e-05,
344
- "loss": 2.7662,
345
  "step": 7000
346
  },
347
  {
348
  "epoch": 1.39,
349
  "eval_COMMENT": {
350
- "f1": 0.6726807593914097,
351
- "number": 6922,
352
- "precision": 0.6298537569339385,
353
- "recall": 0.7217567177116441
354
  },
355
  "eval_NAME": {
356
- "f1": 0.8074248541947062,
357
- "number": 8833,
358
- "precision": 0.7999777753083676,
359
- "recall": 0.8150118872410279
360
  },
361
  "eval_QTY": {
362
- "f1": 0.9814136862855534,
363
- "number": 7092,
364
- "precision": 0.9800337457817773,
365
- "recall": 0.9827975183305132
366
  },
367
  "eval_RANGE_END": {
368
- "f1": 0.7358490566037735,
369
- "number": 88,
370
- "precision": 0.6290322580645161,
371
- "recall": 0.8863636363636364
372
  },
373
  "eval_UNIT": {
374
- "f1": 0.9479758974794195,
375
- "number": 5707,
376
- "precision": 0.9191902567478605,
377
- "recall": 0.9786227439985982
378
- },
379
- "eval_loss": 2.862208366394043,
380
- "eval_overall_accuracy": 0.8235360764393753,
381
- "eval_overall_f1": 0.8432707820327757,
382
- "eval_overall_precision": 0.8209503025493503,
383
- "eval_overall_recall": 0.8668389078974932,
384
- "eval_runtime": 9.9331,
385
- "eval_samples_per_second": 856.327,
386
- "eval_steps_per_second": 26.779,
387
  "step": 7000
388
  },
389
  {
390
  "epoch": 1.48,
391
- "learning_rate": 2.5252425262324292e-05,
392
- "loss": 2.8259,
393
  "step": 7500
394
  },
395
  {
396
  "epoch": 1.58,
397
- "learning_rate": 2.3602586946479245e-05,
398
- "loss": 2.7839,
399
  "step": 8000
400
  },
401
  {
402
  "epoch": 1.58,
403
  "eval_COMMENT": {
404
- "f1": 0.6755974419387412,
405
- "number": 6922,
406
- "precision": 0.6325475860330266,
407
- "recall": 0.7249349898873158
408
  },
409
  "eval_NAME": {
410
- "f1": 0.8115015974440895,
411
- "number": 8833,
412
- "precision": 0.8036190053285968,
413
- "recall": 0.8195403600135854
414
  },
415
  "eval_QTY": {
416
- "f1": 0.9806342969407802,
417
- "number": 7092,
418
- "precision": 0.975977653631285,
419
- "recall": 0.9853355893965031
420
  },
421
  "eval_RANGE_END": {
422
- "f1": 0.7389162561576356,
423
- "number": 88,
424
- "precision": 0.6521739130434783,
425
- "recall": 0.8522727272727273
426
  },
427
  "eval_UNIT": {
428
- "f1": 0.9483591961332994,
429
- "number": 5707,
430
- "precision": 0.9188301018731515,
431
- "recall": 0.9798493078675311
432
- },
433
- "eval_loss": 2.780142307281494,
434
- "eval_overall_accuracy": 0.8241969900107634,
435
- "eval_overall_f1": 0.8452768729641694,
436
- "eval_overall_precision": 0.8221239522143753,
437
- "eval_overall_recall": 0.8697716639899449,
438
- "eval_runtime": 15.1544,
439
- "eval_samples_per_second": 561.289,
440
- "eval_steps_per_second": 17.553,
441
  "step": 8000
442
  },
443
  {
444
  "epoch": 1.68,
445
- "learning_rate": 2.19527486306342e-05,
446
- "loss": 2.7185,
447
  "step": 8500
448
  },
449
  {
450
  "epoch": 1.78,
451
- "learning_rate": 2.0302910314789152e-05,
452
- "loss": 2.7221,
453
  "step": 9000
454
  },
455
  {
456
  "epoch": 1.78,
457
  "eval_COMMENT": {
458
- "f1": 0.690339005761758,
459
- "number": 6922,
460
- "precision": 0.6436781609195402,
461
- "recall": 0.7442935567754985
462
  },
463
  "eval_NAME": {
464
- "f1": 0.8162713392303792,
465
- "number": 8833,
466
- "precision": 0.8124719605204127,
467
- "recall": 0.8201064191101551
468
  },
469
  "eval_QTY": {
470
- "f1": 0.9827975183305132,
471
- "number": 7092,
472
- "precision": 0.9827975183305132,
473
- "recall": 0.9827975183305132
474
  },
475
  "eval_RANGE_END": {
476
- "f1": 0.7336683417085428,
477
- "number": 88,
478
- "precision": 0.6576576576576577,
479
- "recall": 0.8295454545454546
480
  },
481
  "eval_UNIT": {
482
- "f1": 0.9494640122511486,
483
- "number": 5707,
484
- "precision": 0.9227716222920457,
485
- "recall": 0.9777466269493604
486
- },
487
- "eval_loss": 2.7520177364349365,
488
- "eval_overall_accuracy": 0.8285401363370282,
489
- "eval_overall_f1": 0.850812759300823,
490
- "eval_overall_precision": 0.8292674842558834,
491
- "eval_overall_recall": 0.8735074366315202,
492
- "eval_runtime": 11.6589,
493
- "eval_samples_per_second": 729.574,
494
- "eval_steps_per_second": 22.815,
495
  "step": 9000
496
  },
497
  {
498
  "epoch": 1.88,
499
- "learning_rate": 1.8653071998944105e-05,
500
- "loss": 2.8004,
501
  "step": 9500
502
  },
503
  {
504
  "epoch": 1.98,
505
- "learning_rate": 1.700323368309906e-05,
506
- "loss": 2.7156,
507
  "step": 10000
508
  },
509
  {
510
  "epoch": 1.98,
511
  "eval_COMMENT": {
512
- "f1": 0.6864177489177489,
513
- "number": 6922,
514
- "precision": 0.6453828542355635,
515
- "recall": 0.7330251372435712
516
  },
517
  "eval_NAME": {
518
- "f1": 0.8142527960433878,
519
- "number": 8833,
520
- "precision": 0.8084821428571428,
521
- "recall": 0.8201064191101551
522
  },
523
  "eval_QTY": {
524
- "f1": 0.9826589595375722,
525
- "number": 7092,
526
- "precision": 0.9825204398082887,
527
- "recall": 0.9827975183305132
528
  },
529
  "eval_RANGE_END": {
530
- "f1": 0.7219512195121951,
531
- "number": 88,
532
- "precision": 0.6324786324786325,
533
- "recall": 0.8409090909090909
534
  },
535
  "eval_UNIT": {
536
- "f1": 0.9496769806188372,
537
- "number": 5707,
538
- "precision": 0.9222387320455672,
539
- "recall": 0.9787979674084458
540
- },
541
- "eval_loss": 2.7235608100891113,
542
- "eval_overall_accuracy": 0.8264629793983799,
543
- "eval_overall_f1": 0.8495539058775454,
544
- "eval_overall_precision": 0.8291126620139582,
545
- "eval_overall_recall": 0.8710285594581384,
546
- "eval_runtime": 10.9292,
547
- "eval_samples_per_second": 778.285,
548
- "eval_steps_per_second": 24.339,
549
  "step": 10000
550
  },
551
  {
552
  "epoch": 2.08,
553
- "learning_rate": 1.535339536725401e-05,
554
- "loss": 2.6908,
555
  "step": 10500
556
  },
557
  {
558
  "epoch": 2.18,
559
- "learning_rate": 1.3703557051408963e-05,
560
- "loss": 2.6804,
561
  "step": 11000
562
  },
563
  {
564
  "epoch": 2.18,
565
  "eval_COMMENT": {
566
- "f1": 0.6895951823352291,
567
- "number": 6922,
568
- "precision": 0.6422784494578088,
569
- "recall": 0.7444380236925744
570
  },
571
  "eval_NAME": {
572
- "f1": 0.8174098858460327,
573
- "number": 8833,
574
- "precision": 0.8120670391061453,
575
- "recall": 0.8228235027736895
576
  },
577
  "eval_QTY": {
578
- "f1": 0.9829240756421113,
579
- "number": 7092,
580
- "precision": 0.9837570621468926,
581
- "recall": 0.9820924985899605
582
  },
583
  "eval_RANGE_END": {
584
- "f1": 0.7281553398058253,
585
- "number": 88,
586
- "precision": 0.635593220338983,
587
- "recall": 0.8522727272727273
588
  },
589
  "eval_UNIT": {
590
- "f1": 0.9503232391970058,
591
- "number": 5707,
592
- "precision": 0.9234584228798148,
593
- "recall": 0.9787979674084458
594
- },
595
- "eval_loss": 2.692896604537964,
596
- "eval_overall_accuracy": 0.8278792227656401,
597
- "eval_overall_f1": 0.8510414189120316,
598
- "eval_overall_precision": 0.8288219722038385,
599
- "eval_overall_recall": 0.8744850219956707,
600
- "eval_runtime": 9.5517,
601
- "eval_samples_per_second": 890.518,
602
- "eval_steps_per_second": 27.848,
603
  "step": 11000
604
  },
605
  {
606
  "epoch": 2.28,
607
- "learning_rate": 1.2053718735563915e-05,
608
- "loss": 2.5859,
609
  "step": 11500
610
  },
611
  {
612
  "epoch": 2.38,
613
- "learning_rate": 1.0403880419718868e-05,
614
- "loss": 2.6121,
615
  "step": 12000
616
  },
617
  {
618
  "epoch": 2.38,
619
  "eval_COMMENT": {
620
- "f1": 0.691554715452643,
621
- "number": 6922,
622
- "precision": 0.6490939044481054,
623
- "recall": 0.7399595492632187
624
  },
625
  "eval_NAME": {
626
- "f1": 0.8156028368794326,
627
- "number": 8833,
628
- "precision": 0.811037725288257,
629
- "recall": 0.820219630929469
630
  },
631
  "eval_QTY": {
632
- "f1": 0.9826362038664324,
633
- "number": 7092,
634
- "precision": 0.9798121407542408,
635
- "recall": 0.9854765933446137
636
  },
637
  "eval_RANGE_END": {
638
- "f1": 0.7499999999999999,
639
- "number": 88,
640
- "precision": 0.6328125,
641
- "recall": 0.9204545454545454
642
  },
643
  "eval_UNIT": {
644
- "f1": 0.9497709146444936,
645
- "number": 5707,
646
- "precision": 0.9207106431978944,
647
- "recall": 0.9807254249167688
648
- },
649
- "eval_loss": 2.669058322906494,
650
- "eval_overall_accuracy": 0.8276526238268784,
651
- "eval_overall_f1": 0.8514097200965888,
652
- "eval_overall_precision": 0.8299297175440923,
653
- "eval_overall_recall": 0.8740311430766008,
654
- "eval_runtime": 10.4859,
655
- "eval_samples_per_second": 811.181,
656
- "eval_steps_per_second": 25.367,
657
  "step": 12000
658
  },
659
  {
660
  "epoch": 2.47,
661
- "learning_rate": 8.75404210387382e-06,
662
- "loss": 2.6392,
663
  "step": 12500
664
  },
665
  {
666
  "epoch": 2.57,
667
- "learning_rate": 7.104203788028774e-06,
668
- "loss": 2.553,
669
  "step": 13000
670
  },
671
  {
672
  "epoch": 2.57,
673
  "eval_COMMENT": {
674
- "f1": 0.6915875260995488,
675
- "number": 6922,
676
- "precision": 0.6478233438485804,
677
- "recall": 0.7416931522681306
678
  },
679
  "eval_NAME": {
680
- "f1": 0.8171171171171171,
681
- "number": 8833,
682
- "precision": 0.8128150554497592,
683
- "recall": 0.8214649609419223
684
  },
685
  "eval_QTY": {
686
- "f1": 0.9832299887260428,
687
- "number": 7092,
688
- "precision": 0.9826760563380281,
689
- "recall": 0.983784545967287
690
  },
691
  "eval_RANGE_END": {
692
- "f1": 0.742857142857143,
693
- "number": 88,
694
- "precision": 0.639344262295082,
695
- "recall": 0.8863636363636364
696
  },
697
  "eval_UNIT": {
698
- "f1": 0.9500635862653668,
699
- "number": 5707,
700
- "precision": 0.920335085413929,
701
- "recall": 0.9817767653758542
702
- },
703
- "eval_loss": 2.6652376651763916,
704
- "eval_overall_accuracy": 0.8286912022962026,
705
- "eval_overall_f1": 0.8519148357254608,
706
- "eval_overall_precision": 0.8304489092235263,
707
- "eval_overall_recall": 0.874519935758676,
708
- "eval_runtime": 11.1046,
709
- "eval_samples_per_second": 765.987,
710
- "eval_steps_per_second": 23.954,
711
  "step": 13000
712
  },
713
  {
714
  "epoch": 2.67,
715
- "learning_rate": 5.4543654721837265e-06,
716
- "loss": 2.5782,
717
  "step": 13500
718
  },
719
  {
720
  "epoch": 2.77,
721
- "learning_rate": 3.804527156338679e-06,
722
- "loss": 2.5781,
723
  "step": 14000
724
  },
725
  {
726
  "epoch": 2.77,
727
  "eval_COMMENT": {
728
- "f1": 0.6930304873926858,
729
- "number": 6922,
730
- "precision": 0.6512514292974209,
731
- "recall": 0.7405374169315226
732
  },
733
  "eval_NAME": {
734
- "f1": 0.8163609767075503,
735
- "number": 8833,
736
- "precision": 0.8114304887596465,
737
- "recall": 0.8213517491226084
738
  },
739
  "eval_QTY": {
740
- "f1": 0.9833638798815735,
741
- "number": 7092,
742
- "precision": 0.9832252607837609,
743
- "recall": 0.983502538071066
744
  },
745
  "eval_RANGE_END": {
746
- "f1": 0.7450980392156864,
747
- "number": 88,
748
- "precision": 0.6551724137931034,
749
- "recall": 0.8636363636363636
750
  },
751
  "eval_UNIT": {
752
- "f1": 0.9503184713375797,
753
- "number": 5707,
754
- "precision": 0.9220500988793672,
755
- "recall": 0.9803749780970737
756
- },
757
- "eval_loss": 2.6431026458740234,
758
- "eval_overall_accuracy": 0.8285967860717186,
759
- "eval_overall_f1": 0.8522440918068515,
760
- "eval_overall_precision": 0.8317381189764042,
761
- "eval_overall_recall": 0.8737867467355631,
762
- "eval_runtime": 10.2487,
763
- "eval_samples_per_second": 829.962,
764
- "eval_steps_per_second": 25.955,
765
  "step": 14000
766
  },
767
  {
768
  "epoch": 2.87,
769
- "learning_rate": 2.154688840493632e-06,
770
- "loss": 2.5714,
771
  "step": 14500
772
  },
773
  {
774
  "epoch": 2.97,
775
- "learning_rate": 5.048505246485845e-07,
776
- "loss": 2.5928,
777
  "step": 15000
778
  },
779
  {
780
  "epoch": 2.97,
781
  "eval_COMMENT": {
782
- "f1": 0.6959701997968167,
783
- "number": 6922,
784
- "precision": 0.6551064643631264,
785
- "recall": 0.7422710199364345
786
  },
787
  "eval_NAME": {
788
- "f1": 0.8171788810086682,
789
- "number": 8833,
790
- "precision": 0.8126049479458188,
791
- "recall": 0.8218045963998641
792
  },
793
  "eval_QTY": {
794
- "f1": 0.9831607130275488,
795
- "number": 7092,
796
- "precision": 0.9825376707505985,
797
- "recall": 0.983784545967287
798
  },
799
  "eval_RANGE_END": {
800
- "f1": 0.7439613526570048,
801
- "number": 88,
802
- "precision": 0.6470588235294118,
803
- "recall": 0.875
804
  },
805
  "eval_UNIT": {
806
- "f1": 0.9497833290848839,
807
- "number": 5707,
808
- "precision": 0.9219729462223688,
809
- "recall": 0.9793236376379885
810
- },
811
- "eval_loss": 2.639442205429077,
812
- "eval_overall_accuracy": 0.8289178012349642,
813
- "eval_overall_f1": 0.8531516183986372,
814
- "eval_overall_precision": 0.8330560915563244,
815
- "eval_overall_recall": 0.874240625654633,
816
- "eval_runtime": 9.6239,
817
- "eval_samples_per_second": 883.843,
818
- "eval_steps_per_second": 27.64,
819
  "step": 15000
820
  },
821
  {
822
- "epoch": 3.0,
823
- "step": 15153,
824
- "total_flos": 466306211114724.0,
825
- "train_loss": 3.047607653480721,
826
- "train_runtime": 1056.0535,
827
- "train_samples_per_second": 459.076,
828
- "train_steps_per_second": 14.349
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
829
  }
830
  ],
831
  "logging_steps": 500,
832
- "max_steps": 15153,
833
- "num_train_epochs": 3,
834
- "save_steps": 500,
835
- "total_flos": 466306211114724.0,
836
  "trial_name": null,
837
  "trial_params": null
838
  }
 
1
  {
2
+ "best_metric": 2.1034367084503174,
3
+ "best_model_checkpoint": "nyt_ingredients-crf-tagger-gte-small-L3-ingredient-v2/checkpoint-40000",
4
+ "epoch": 10.0,
5
  "eval_steps": 1000,
6
+ "global_step": 50510,
7
  "is_hyper_param_search": false,
8
  "is_local_process_zero": true,
9
  "is_world_process_zero": true,
10
  "log_history": [
11
  {
12
  "epoch": 0.1,
13
+ "learning_rate": 4.9505048505246485e-05,
14
+ "loss": 6.8194,
15
  "step": 500
16
  },
17
  {
18
  "epoch": 0.2,
19
+ "learning_rate": 4.9010097010492975e-05,
20
+ "loss": 4.134,
21
  "step": 1000
22
  },
23
  {
24
  "epoch": 0.2,
25
  "eval_COMMENT": {
26
+ "f1": 0.5763258721516435,
27
+ "number": 6854,
28
+ "precision": 0.5343387760189455,
29
+ "recall": 0.6254741756638459
30
  },
31
  "eval_NAME": {
32
+ "f1": 0.78330041694097,
33
+ "number": 8845,
34
+ "precision": 0.7608440797186401,
35
+ "recall": 0.8071226681741097
36
  },
37
  "eval_QTY": {
38
+ "f1": 0.9729431253451132,
39
+ "number": 7152,
40
+ "precision": 0.960741548527808,
41
+ "recall": 0.9854586129753915
42
  },
43
  "eval_RANGE_END": {
44
  "f1": 0.0,
45
+ "number": 105,
46
  "precision": 0.0,
47
  "recall": 0.0
48
  },
49
  "eval_UNIT": {
50
+ "f1": 0.9476944253269098,
51
+ "number": 5646,
52
+ "precision": 0.921378387420542,
53
+ "recall": 0.975557917109458
54
+ },
55
+ "eval_loss": 3.7770841121673584,
56
+ "eval_overall_accuracy": 0.7948864068079933,
57
+ "eval_overall_f1": 0.8085364620208354,
58
+ "eval_overall_precision": 0.7806640625,
59
+ "eval_overall_recall": 0.8384728340675477,
60
+ "eval_runtime": 11.1289,
61
+ "eval_samples_per_second": 764.316,
62
+ "eval_steps_per_second": 23.902,
63
  "step": 1000
64
  },
65
  {
66
  "epoch": 0.3,
67
+ "learning_rate": 4.851514551573946e-05,
68
+ "loss": 3.7402,
69
  "step": 1500
70
  },
71
  {
72
  "epoch": 0.4,
73
+ "learning_rate": 4.802019402098595e-05,
74
+ "loss": 3.5226,
75
  "step": 2000
76
  },
77
  {
78
  "epoch": 0.4,
79
  "eval_COMMENT": {
80
+ "f1": 0.6215112776922562,
81
+ "number": 6854,
82
+ "precision": 0.5741313218746136,
83
+ "recall": 0.6774146483805077
84
  },
85
  "eval_NAME": {
86
+ "f1": 0.7914056489724146,
87
+ "number": 8845,
88
+ "precision": 0.7699133967710895,
89
+ "recall": 0.8141322781232334
90
  },
91
  "eval_QTY": {
92
+ "f1": 0.9796598403332176,
93
+ "number": 7152,
94
+ "precision": 0.9728388253136633,
95
+ "recall": 0.9865771812080537
96
  },
97
  "eval_RANGE_END": {
98
+ "f1": 0.6425339366515838,
99
+ "number": 105,
100
+ "precision": 0.6120689655172413,
101
+ "recall": 0.6761904761904762
102
+ },
103
+ "eval_UNIT": {
104
+ "f1": 0.9472432248746921,
105
+ "number": 5646,
106
+ "precision": 0.9102040816326531,
107
+ "recall": 0.9874247254693589
108
+ },
109
+ "eval_loss": 3.3654797077178955,
110
+ "eval_overall_accuracy": 0.8063976901451257,
111
+ "eval_overall_f1": 0.8245767266863746,
112
+ "eval_overall_precision": 0.7934958298312537,
113
+ "eval_overall_recall": 0.8581917348437172,
114
+ "eval_runtime": 11.014,
115
+ "eval_samples_per_second": 772.292,
116
+ "eval_steps_per_second": 24.151,
117
  "step": 2000
118
  },
119
  {
120
  "epoch": 0.49,
121
+ "learning_rate": 4.752524252623243e-05,
122
+ "loss": 3.3189,
123
  "step": 2500
124
  },
125
  {
126
  "epoch": 0.59,
127
+ "learning_rate": 4.703029103147892e-05,
128
+ "loss": 3.1948,
129
  "step": 3000
130
  },
131
  {
132
  "epoch": 0.59,
133
  "eval_COMMENT": {
134
+ "f1": 0.6503977349332615,
135
+ "number": 6854,
136
+ "precision": 0.6045112781954888,
137
+ "recall": 0.7038225853516195
138
  },
139
  "eval_NAME": {
140
+ "f1": 0.8008250181169521,
141
+ "number": 8845,
142
+ "precision": 0.7898614471079833,
143
+ "recall": 0.8120972300734879
144
  },
145
  "eval_QTY": {
146
+ "f1": 0.9830792896098447,
147
+ "number": 7152,
148
+ "precision": 0.9832167832167832,
149
+ "recall": 0.9829418344519015
150
  },
151
  "eval_RANGE_END": {
152
+ "f1": 0.7035573122529643,
153
+ "number": 105,
154
+ "precision": 0.6013513513513513,
155
+ "recall": 0.8476190476190476
156
  },
157
  "eval_UNIT": {
158
+ "f1": 0.9492858975455399,
159
+ "number": 5646,
160
+ "precision": 0.9178104845377874,
161
+ "recall": 0.9829968119022316
162
+ },
163
+ "eval_loss": 3.1104416847229004,
164
+ "eval_overall_accuracy": 0.8160474128105767,
165
+ "eval_overall_f1": 0.8361769539655378,
166
+ "eval_overall_precision": 0.8112035241132187,
167
+ "eval_overall_recall": 0.8627368715474443,
168
+ "eval_runtime": 9.4851,
169
+ "eval_samples_per_second": 896.774,
170
+ "eval_steps_per_second": 28.044,
171
  "step": 3000
172
  },
173
  {
174
  "epoch": 0.69,
175
+ "learning_rate": 4.65353395367254e-05,
176
+ "loss": 3.1131,
177
  "step": 3500
178
  },
179
  {
180
  "epoch": 0.79,
181
+ "learning_rate": 4.6040388041971886e-05,
182
+ "loss": 3.0233,
183
  "step": 4000
184
  },
185
  {
186
  "epoch": 0.79,
187
  "eval_COMMENT": {
188
+ "f1": 0.6598611678236015,
189
+ "number": 6854,
190
+ "precision": 0.6183673469387755,
191
+ "recall": 0.7073241902538664
192
  },
193
  "eval_NAME": {
194
+ "f1": 0.8091748251748251,
195
+ "number": 8845,
196
+ "precision": 0.8008859357696567,
197
+ "recall": 0.8176370830977954
198
  },
199
  "eval_QTY": {
200
+ "f1": 0.9835126449629734,
201
+ "number": 7152,
202
+ "precision": 0.982826026249651,
203
+ "recall": 0.9842002237136466
204
  },
205
  "eval_RANGE_END": {
206
+ "f1": 0.5851063829787234,
207
+ "number": 105,
208
+ "precision": 0.6626506024096386,
209
+ "recall": 0.5238095238095238
210
  },
211
  "eval_UNIT": {
212
+ "f1": 0.9505612201182417,
213
+ "number": 5646,
214
+ "precision": 0.9206639004149377,
215
+ "recall": 0.9824654622741764
216
+ },
217
+ "eval_loss": 3.005340576171875,
218
+ "eval_overall_accuracy": 0.8174150900387509,
219
+ "eval_overall_f1": 0.8416805692690068,
220
+ "eval_overall_precision": 0.8202057067020571,
221
+ "eval_overall_recall": 0.8643101880987344,
222
+ "eval_runtime": 11.0513,
223
+ "eval_samples_per_second": 769.68,
224
+ "eval_steps_per_second": 24.069,
225
  "step": 4000
226
  },
227
  {
228
  "epoch": 0.89,
229
+ "learning_rate": 4.5545436547218376e-05,
230
+ "loss": 2.9721,
231
  "step": 4500
232
  },
233
  {
234
  "epoch": 0.99,
235
+ "learning_rate": 4.505048505246486e-05,
236
+ "loss": 2.9567,
237
  "step": 5000
238
  },
239
  {
240
  "epoch": 0.99,
241
  "eval_COMMENT": {
242
+ "f1": 0.677434679334917,
243
+ "number": 6854,
244
+ "precision": 0.633295267098084,
245
+ "recall": 0.7281879194630873
246
  },
247
  "eval_NAME": {
248
+ "f1": 0.8113767426235933,
249
+ "number": 8845,
250
+ "precision": 0.8036823425022183,
251
+ "recall": 0.8192198982475976
252
  },
253
  "eval_QTY": {
254
+ "f1": 0.9826323498639883,
255
+ "number": 7152,
256
+ "precision": 0.9803757828810021,
257
+ "recall": 0.9848993288590604
258
  },
259
  "eval_RANGE_END": {
260
+ "f1": 0.6288659793814434,
261
+ "number": 105,
262
+ "precision": 0.6853932584269663,
263
+ "recall": 0.580952380952381
264
  },
265
  "eval_UNIT": {
266
+ "f1": 0.9479768786127167,
267
+ "number": 5646,
268
+ "precision": 0.9114089571755476,
269
+ "recall": 0.9876018420120439
270
+ },
271
+ "eval_loss": 2.910010814666748,
272
+ "eval_overall_accuracy": 0.8215941037915052,
273
+ "eval_overall_f1": 0.8462413611587509,
274
+ "eval_overall_precision": 0.8226748984779954,
275
+ "eval_overall_recall": 0.8711978183343823,
276
+ "eval_runtime": 11.1963,
277
+ "eval_samples_per_second": 759.713,
278
+ "eval_steps_per_second": 23.758,
279
  "step": 5000
280
  },
281
  {
282
  "epoch": 1.09,
283
+ "learning_rate": 4.455553355771135e-05,
284
+ "loss": 2.794,
285
  "step": 5500
286
  },
287
  {
288
  "epoch": 1.19,
289
+ "learning_rate": 4.406058206295783e-05,
290
+ "loss": 2.738,
291
  "step": 6000
292
  },
293
  {
294
  "epoch": 1.19,
295
  "eval_COMMENT": {
296
+ "f1": 0.6844883595018949,
297
+ "number": 6854,
298
+ "precision": 0.6383489017924766,
299
+ "recall": 0.7378173329442661
300
  },
301
  "eval_NAME": {
302
+ "f1": 0.809906216656371,
303
+ "number": 8845,
304
+ "precision": 0.8046195045748716,
305
+ "recall": 0.8152628603730921
306
  },
307
  "eval_QTY": {
308
+ "f1": 0.9817170663885992,
309
+ "number": 7152,
310
+ "precision": 0.9762201023088621,
311
+ "recall": 0.9872762863534675
312
  },
313
  "eval_RANGE_END": {
314
+ "f1": 0.7286821705426357,
315
+ "number": 105,
316
+ "precision": 0.6143790849673203,
317
+ "recall": 0.8952380952380953
318
  },
319
  "eval_UNIT": {
320
+ "f1": 0.9514546393527284,
321
+ "number": 5646,
322
+ "precision": 0.9254855994641661,
323
+ "recall": 0.9789231314204747
324
+ },
325
+ "eval_loss": 2.8514182567596436,
326
+ "eval_overall_accuracy": 0.8213471620697516,
327
+ "eval_overall_f1": 0.8480048942967846,
328
+ "eval_overall_precision": 0.8250115733086436,
329
+ "eval_overall_recall": 0.8723166212152996,
330
+ "eval_runtime": 8.7005,
331
+ "eval_samples_per_second": 977.64,
332
+ "eval_steps_per_second": 30.573,
333
  "step": 6000
334
  },
335
  {
336
  "epoch": 1.29,
337
+ "learning_rate": 4.356563056820432e-05,
338
+ "loss": 2.7896,
339
  "step": 6500
340
  },
341
  {
342
  "epoch": 1.39,
343
+ "learning_rate": 4.3070679073450804e-05,
344
+ "loss": 2.8132,
345
  "step": 7000
346
  },
347
  {
348
  "epoch": 1.39,
349
  "eval_COMMENT": {
350
+ "f1": 0.680542242913871,
351
+ "number": 6854,
352
+ "precision": 0.641124871001032,
353
+ "recall": 0.7251240151736212
354
  },
355
  "eval_NAME": {
356
+ "f1": 0.8072829131652661,
357
+ "number": 8845,
358
+ "precision": 0.8001110494169905,
359
+ "recall": 0.814584511023177
360
  },
361
  "eval_QTY": {
362
+ "f1": 0.9839452743263996,
363
+ "number": 7152,
364
+ "precision": 0.9824365765263451,
365
+ "recall": 0.9854586129753915
366
  },
367
  "eval_RANGE_END": {
368
+ "f1": 0.7421875,
369
+ "number": 105,
370
+ "precision": 0.6291390728476821,
371
+ "recall": 0.9047619047619048
372
  },
373
  "eval_UNIT": {
374
+ "f1": 0.9518423307626392,
375
+ "number": 5646,
376
+ "precision": 0.9219787516600265,
377
+ "recall": 0.983705278072972
378
+ },
379
+ "eval_loss": 2.776045322418213,
380
+ "eval_overall_accuracy": 0.8222589468885343,
381
+ "eval_overall_f1": 0.8473121210056551,
382
+ "eval_overall_precision": 0.8261476117717399,
383
+ "eval_overall_recall": 0.8695895391930635,
384
+ "eval_runtime": 11.1273,
385
+ "eval_samples_per_second": 764.429,
386
+ "eval_steps_per_second": 23.905,
387
  "step": 7000
388
  },
389
  {
390
  "epoch": 1.48,
391
+ "learning_rate": 4.257572757869729e-05,
392
+ "loss": 2.7089,
393
  "step": 7500
394
  },
395
  {
396
  "epoch": 1.58,
397
+ "learning_rate": 4.208077608394378e-05,
398
+ "loss": 2.6976,
399
  "step": 8000
400
  },
401
  {
402
  "epoch": 1.58,
403
  "eval_COMMENT": {
404
+ "f1": 0.6947368421052631,
405
+ "number": 6854,
406
+ "precision": 0.6535493827160493,
407
+ "recall": 0.7414648380507732
408
  },
409
  "eval_NAME": {
410
+ "f1": 0.8145306859205775,
411
+ "number": 8845,
412
+ "precision": 0.8127884723629405,
413
+ "recall": 0.8162803843979649
414
  },
415
  "eval_QTY": {
416
+ "f1": 0.9840759882665177,
417
+ "number": 7152,
418
+ "precision": 0.9831147083449623,
419
+ "recall": 0.9850391498881432
420
  },
421
  "eval_RANGE_END": {
422
+ "f1": 0.75098814229249,
423
+ "number": 105,
424
+ "precision": 0.6418918918918919,
425
+ "recall": 0.9047619047619048
426
  },
427
  "eval_UNIT": {
428
+ "f1": 0.9538461538461539,
429
+ "number": 5646,
430
+ "precision": 0.926531975288028,
431
+ "recall": 0.9828196953595466
432
+ },
433
+ "eval_loss": 2.707292318344116,
434
+ "eval_overall_accuracy": 0.826172023402477,
435
+ "eval_overall_f1": 0.8534594631514241,
436
+ "eval_overall_precision": 0.8340898471397103,
437
+ "eval_overall_recall": 0.8737500874064751,
438
+ "eval_runtime": 10.8076,
439
+ "eval_samples_per_second": 787.041,
440
+ "eval_steps_per_second": 24.612,
441
  "step": 8000
442
  },
443
  {
444
  "epoch": 1.68,
445
+ "learning_rate": 4.158582458919026e-05,
446
+ "loss": 2.6869,
447
  "step": 8500
448
  },
449
  {
450
  "epoch": 1.78,
451
+ "learning_rate": 4.109087309443675e-05,
452
+ "loss": 2.6347,
453
  "step": 9000
454
  },
455
  {
456
  "epoch": 1.78,
457
  "eval_COMMENT": {
458
+ "f1": 0.6949685534591195,
459
+ "number": 6854,
460
+ "precision": 0.6538461538461539,
461
+ "recall": 0.7416107382550335
462
  },
463
  "eval_NAME": {
464
+ "f1": 0.8143807055111011,
465
+ "number": 8845,
466
+ "precision": 0.8118188967531738,
467
+ "recall": 0.8169587337478802
468
  },
469
  "eval_QTY": {
470
+ "f1": 0.9832394464149107,
471
+ "number": 7152,
472
+ "precision": 0.9781375397813754,
473
+ "recall": 0.9883948545861297
474
  },
475
  "eval_RANGE_END": {
476
+ "f1": 0.7588932806324111,
477
+ "number": 105,
478
+ "precision": 0.6486486486486487,
479
+ "recall": 0.9142857142857143
480
  },
481
  "eval_UNIT": {
482
+ "f1": 0.9523400601116359,
483
+ "number": 5646,
484
+ "precision": 0.92432072012002,
485
+ "recall": 0.9821112291888062
486
+ },
487
+ "eval_loss": 2.6447880268096924,
488
+ "eval_overall_accuracy": 0.8236836106678824,
489
+ "eval_overall_f1": 0.8531482839167277,
490
+ "eval_overall_precision": 0.832606742320876,
491
+ "eval_overall_recall": 0.8747290399272778,
492
+ "eval_runtime": 10.4718,
493
+ "eval_samples_per_second": 812.274,
494
+ "eval_steps_per_second": 25.401,
495
  "step": 9000
496
  },
497
  {
498
  "epoch": 1.88,
499
+ "learning_rate": 4.059592159968323e-05,
500
+ "loss": 2.5569,
501
  "step": 9500
502
  },
503
  {
504
  "epoch": 1.98,
505
+ "learning_rate": 4.010097010492972e-05,
506
+ "loss": 2.5847,
507
  "step": 10000
508
  },
509
  {
510
  "epoch": 1.98,
511
  "eval_COMMENT": {
512
+ "f1": 0.6963045290358433,
513
+ "number": 6854,
514
+ "precision": 0.6645452134712277,
515
+ "recall": 0.7312518237525533
516
  },
517
  "eval_NAME": {
518
+ "f1": 0.8156796390298928,
519
+ "number": 8845,
520
+ "precision": 0.8138435565559933,
521
+ "recall": 0.8175240248728095
522
  },
523
  "eval_QTY": {
524
+ "f1": 0.9831476323119777,
525
+ "number": 7152,
526
+ "precision": 0.9793285238623751,
527
+ "recall": 0.986996644295302
528
  },
529
  "eval_RANGE_END": {
530
+ "f1": 0.7639484978540773,
531
+ "number": 105,
532
+ "precision": 0.6953125,
533
+ "recall": 0.8476190476190476
534
  },
535
  "eval_UNIT": {
536
+ "f1": 0.9530017152658663,
537
+ "number": 5646,
538
+ "precision": 0.9238443631526438,
539
+ "recall": 0.9840595111583422
540
+ },
541
+ "eval_loss": 2.591038227081299,
542
+ "eval_overall_accuracy": 0.8253172251348682,
543
+ "eval_overall_f1": 0.8546566402302197,
544
+ "eval_overall_precision": 0.8377942707458776,
545
+ "eval_overall_recall": 0.8722117334452136,
546
+ "eval_runtime": 10.9908,
547
+ "eval_samples_per_second": 773.919,
548
+ "eval_steps_per_second": 24.202,
549
  "step": 10000
550
  },
551
  {
552
  "epoch": 2.08,
553
+ "learning_rate": 3.9606018610176205e-05,
554
+ "loss": 2.5001,
555
  "step": 10500
556
  },
557
  {
558
  "epoch": 2.18,
559
+ "learning_rate": 3.911106711542269e-05,
560
+ "loss": 2.4321,
561
  "step": 11000
562
  },
563
  {
564
  "epoch": 2.18,
565
  "eval_COMMENT": {
566
+ "f1": 0.7009998630324613,
567
+ "number": 6854,
568
+ "precision": 0.660557563242127,
569
+ "recall": 0.7467172454041435
570
  },
571
  "eval_NAME": {
572
+ "f1": 0.8124085125548924,
573
+ "number": 8845,
574
+ "precision": 0.8091286307053942,
575
+ "recall": 0.8157150932730356
576
  },
577
  "eval_QTY": {
578
+ "f1": 0.9833752444816989,
579
+ "number": 7152,
580
+ "precision": 0.9825516471245115,
581
+ "recall": 0.9842002237136466
582
  },
583
  "eval_RANGE_END": {
584
+ "f1": 0.7404580152671757,
585
+ "number": 105,
586
+ "precision": 0.6178343949044586,
587
+ "recall": 0.9238095238095239
588
  },
589
  "eval_UNIT": {
590
+ "f1": 0.9521690767519465,
591
+ "number": 5646,
592
+ "precision": 0.9210395629862606,
593
+ "recall": 0.9854764434998229
594
+ },
595
+ "eval_loss": 2.5731780529022217,
596
+ "eval_overall_accuracy": 0.8255071803054479,
597
+ "eval_overall_f1": 0.8539459994200822,
598
+ "eval_overall_precision": 0.8336830186165785,
599
+ "eval_overall_recall": 0.8752185161876792,
600
+ "eval_runtime": 9.4187,
601
+ "eval_samples_per_second": 903.101,
602
+ "eval_steps_per_second": 28.242,
603
  "step": 11000
604
  },
605
  {
606
  "epoch": 2.28,
607
+ "learning_rate": 3.861611562066917e-05,
608
+ "loss": 2.5117,
609
  "step": 11500
610
  },
611
  {
612
  "epoch": 2.38,
613
+ "learning_rate": 3.812116412591566e-05,
614
+ "loss": 2.4326,
615
  "step": 12000
616
  },
617
  {
618
  "epoch": 2.38,
619
  "eval_COMMENT": {
620
+ "f1": 0.7086570477247504,
621
+ "number": 6854,
622
+ "precision": 0.6754826765405977,
623
+ "recall": 0.7452582433615407
624
  },
625
  "eval_NAME": {
626
+ "f1": 0.8158534516876803,
627
+ "number": 8845,
628
+ "precision": 0.8159918570459173,
629
+ "recall": 0.8157150932730356
630
  },
631
  "eval_QTY": {
632
+ "f1": 0.9844993715961456,
633
+ "number": 7152,
634
+ "precision": 0.9832635983263598,
635
+ "recall": 0.985738255033557
636
  },
637
  "eval_RANGE_END": {
638
+ "f1": 0.7654320987654321,
639
+ "number": 105,
640
+ "precision": 0.6739130434782609,
641
+ "recall": 0.8857142857142857
642
  },
643
  "eval_UNIT": {
644
+ "f1": 0.9534265374388883,
645
+ "number": 5646,
646
+ "precision": 0.9243306169965075,
647
+ "recall": 0.9844137442437123
648
+ },
649
+ "eval_loss": 2.5278468132019043,
650
+ "eval_overall_accuracy": 0.8280525795912165,
651
+ "eval_overall_f1": 0.8580588749635675,
652
+ "eval_overall_precision": 0.8418502943650126,
653
+ "eval_overall_recall": 0.8749038528774211,
654
+ "eval_runtime": 11.4233,
655
+ "eval_samples_per_second": 744.616,
656
+ "eval_steps_per_second": 23.286,
657
  "step": 12000
658
  },
659
  {
660
  "epoch": 2.47,
661
+ "learning_rate": 3.762621263116215e-05,
662
+ "loss": 2.3983,
663
  "step": 12500
664
  },
665
  {
666
  "epoch": 2.57,
667
+ "learning_rate": 3.7131261136408633e-05,
668
+ "loss": 2.3705,
669
  "step": 13000
670
  },
671
  {
672
  "epoch": 2.57,
673
  "eval_COMMENT": {
674
+ "f1": 0.7056559686619477,
675
+ "number": 6854,
676
+ "precision": 0.6670131219955827,
677
+ "recall": 0.7490516486723081
678
  },
679
  "eval_NAME": {
680
+ "f1": 0.8140058545372664,
681
+ "number": 8845,
682
+ "precision": 0.8106289942818702,
683
+ "recall": 0.8174109666478236
684
  },
685
  "eval_QTY": {
686
+ "f1": 0.9845080251221213,
687
+ "number": 7152,
688
+ "precision": 0.9827249930342714,
689
+ "recall": 0.9862975391498882
690
  },
691
  "eval_RANGE_END": {
692
+ "f1": 0.7415730337078652,
693
+ "number": 105,
694
+ "precision": 0.6111111111111112,
695
+ "recall": 0.9428571428571428
696
  },
697
  "eval_UNIT": {
698
+ "f1": 0.952819725279413,
699
+ "number": 5646,
700
+ "precision": 0.9191769547325103,
701
+ "recall": 0.9890187743535246
702
+ },
703
+ "eval_loss": 2.4818899631500244,
704
+ "eval_overall_accuracy": 0.8270458171871439,
705
+ "eval_overall_f1": 0.8562072552999164,
706
+ "eval_overall_precision": 0.8358363024874297,
707
+ "eval_overall_recall": 0.8775959723096287,
708
+ "eval_runtime": 9.7776,
709
+ "eval_samples_per_second": 869.945,
710
+ "eval_steps_per_second": 27.205,
711
  "step": 13000
712
  },
713
  {
714
  "epoch": 2.67,
715
+ "learning_rate": 3.663630964165512e-05,
716
+ "loss": 2.4183,
717
  "step": 13500
718
  },
719
  {
720
  "epoch": 2.77,
721
+ "learning_rate": 3.6141358146901606e-05,
722
+ "loss": 2.364,
723
  "step": 14000
724
  },
725
  {
726
  "epoch": 2.77,
727
  "eval_COMMENT": {
728
+ "f1": 0.7068350260774088,
729
+ "number": 6854,
730
+ "precision": 0.6672713138118683,
731
+ "recall": 0.7513860519404727
732
  },
733
  "eval_NAME": {
734
+ "f1": 0.8130456824198727,
735
+ "number": 8845,
736
+ "precision": 0.8101706331387517,
737
+ "recall": 0.8159412097230073
738
  },
739
  "eval_QTY": {
740
+ "f1": 0.9847269684078387,
741
+ "number": 7152,
742
+ "precision": 0.9823292055099485,
743
+ "recall": 0.9871364653243848
744
  },
745
  "eval_RANGE_END": {
746
+ "f1": 0.7729083665338645,
747
+ "number": 105,
748
+ "precision": 0.6643835616438356,
749
+ "recall": 0.9238095238095239
750
  },
751
  "eval_UNIT": {
752
+ "f1": 0.9542999228328902,
753
+ "number": 5646,
754
+ "precision": 0.9248795080604952,
755
+ "recall": 0.9856535600425079
756
+ },
757
+ "eval_loss": 2.4206130504608154,
758
+ "eval_overall_accuracy": 0.8284704809664919,
759
+ "eval_overall_f1": 0.8566014544709617,
760
+ "eval_overall_precision": 0.8369695756605284,
761
+ "eval_overall_recall": 0.8771764212292846,
762
+ "eval_runtime": 10.6958,
763
+ "eval_samples_per_second": 795.265,
764
+ "eval_steps_per_second": 24.87,
765
  "step": 14000
766
  },
767
  {
768
  "epoch": 2.87,
769
+ "learning_rate": 3.564640665214809e-05,
770
+ "loss": 2.3089,
771
  "step": 14500
772
  },
773
  {
774
  "epoch": 2.97,
775
+ "learning_rate": 3.515145515739457e-05,
776
+ "loss": 2.3349,
777
  "step": 15000
778
  },
779
  {
780
  "epoch": 2.97,
781
  "eval_COMMENT": {
782
+ "f1": 0.7115305703734099,
783
+ "number": 6854,
784
+ "precision": 0.6696704428424305,
785
+ "recall": 0.7589728625620076
786
  },
787
  "eval_NAME": {
788
+ "f1": 0.8152284263959392,
789
+ "number": 8845,
790
+ "precision": 0.8133933595948227,
791
+ "recall": 0.8170717919728661
792
  },
793
  "eval_QTY": {
794
+ "f1": 0.9854223338215806,
795
+ "number": 7152,
796
+ "precision": 0.9831593597773138,
797
+ "recall": 0.9876957494407159
798
  },
799
  "eval_RANGE_END": {
800
+ "f1": 0.7320754716981133,
801
+ "number": 105,
802
+ "precision": 0.60625,
803
+ "recall": 0.9238095238095239
804
  },
805
  "eval_UNIT": {
806
+ "f1": 0.954592186429061,
807
+ "number": 5646,
808
+ "precision": 0.9244938599402589,
809
+ "recall": 0.9867162592986185
810
+ },
811
+ "eval_loss": 2.390350103378296,
812
+ "eval_overall_accuracy": 0.8285084720006078,
813
+ "eval_overall_f1": 0.8583563606590933,
814
+ "eval_overall_precision": 0.8380295763389288,
815
+ "eval_overall_recall": 0.8796937277113489,
816
+ "eval_runtime": 13.4662,
817
+ "eval_samples_per_second": 631.657,
818
+ "eval_steps_per_second": 19.753,
819
  "step": 15000
820
  },
821
  {
822
+ "epoch": 3.07,
823
+ "learning_rate": 3.465650366264107e-05,
824
+ "loss": 2.251,
825
+ "step": 15500
826
+ },
827
+ {
828
+ "epoch": 3.17,
829
+ "learning_rate": 3.416155216788755e-05,
830
+ "loss": 2.253,
831
+ "step": 16000
832
+ },
833
+ {
834
+ "epoch": 3.17,
835
+ "eval_COMMENT": {
836
+ "f1": 0.7120891136472357,
837
+ "number": 6854,
838
+ "precision": 0.669751896130608,
839
+ "recall": 0.7601400641960899
840
+ },
841
+ "eval_NAME": {
842
+ "f1": 0.8165914221218961,
843
+ "number": 8845,
844
+ "precision": 0.8152112676056338,
845
+ "recall": 0.817976257772753
846
+ },
847
+ "eval_QTY": {
848
+ "f1": 0.9850704618389843,
849
+ "number": 7152,
850
+ "precision": 0.9830130882762461,
851
+ "recall": 0.9871364653243848
852
+ },
853
+ "eval_RANGE_END": {
854
+ "f1": 0.7529411764705883,
855
+ "number": 105,
856
+ "precision": 0.64,
857
+ "recall": 0.9142857142857143
858
+ },
859
+ "eval_UNIT": {
860
+ "f1": 0.9538013199622868,
861
+ "number": 5646,
862
+ "precision": 0.924098986879256,
863
+ "recall": 0.9854764434998229
864
+ },
865
+ "eval_loss": 2.3770651817321777,
866
+ "eval_overall_accuracy": 0.8302180685358256,
867
+ "eval_overall_f1": 0.8587418314593322,
868
+ "eval_overall_precision": 0.8386376512147166,
869
+ "eval_overall_recall": 0.8798335780714636,
870
+ "eval_runtime": 11.0556,
871
+ "eval_samples_per_second": 769.382,
872
+ "eval_steps_per_second": 24.06,
873
+ "step": 16000
874
+ },
875
+ {
876
+ "epoch": 3.27,
877
+ "learning_rate": 3.3666600673134034e-05,
878
+ "loss": 2.1955,
879
+ "step": 16500
880
+ },
881
+ {
882
+ "epoch": 3.37,
883
+ "learning_rate": 3.317164917838052e-05,
884
+ "loss": 2.2137,
885
+ "step": 17000
886
+ },
887
+ {
888
+ "epoch": 3.37,
889
+ "eval_COMMENT": {
890
+ "f1": 0.7152373022481265,
891
+ "number": 6854,
892
+ "precision": 0.6819264355649642,
893
+ "recall": 0.7519696527575138
894
+ },
895
+ "eval_NAME": {
896
+ "f1": 0.816918906708832,
897
+ "number": 8845,
898
+ "precision": 0.8160893602617624,
899
+ "recall": 0.8177501413227812
900
+ },
901
+ "eval_QTY": {
902
+ "f1": 0.9852099902330124,
903
+ "number": 7152,
904
+ "precision": 0.9831523252575884,
905
+ "recall": 0.9872762863534675
906
+ },
907
+ "eval_RANGE_END": {
908
+ "f1": 0.7619047619047618,
909
+ "number": 105,
910
+ "precision": 0.6530612244897959,
911
+ "recall": 0.9142857142857143
912
+ },
913
+ "eval_UNIT": {
914
+ "f1": 0.9529855868222373,
915
+ "number": 5646,
916
+ "precision": 0.924126455906822,
917
+ "recall": 0.983705278072972
918
+ },
919
+ "eval_loss": 2.378207206726074,
920
+ "eval_overall_accuracy": 0.8285464630347238,
921
+ "eval_overall_f1": 0.8600801891641822,
922
+ "eval_overall_precision": 0.8433467741935484,
923
+ "eval_overall_recall": 0.8774910845395427,
924
+ "eval_runtime": 10.7102,
925
+ "eval_samples_per_second": 794.197,
926
+ "eval_steps_per_second": 24.836,
927
+ "step": 17000
928
+ },
929
+ {
930
+ "epoch": 3.46,
931
+ "learning_rate": 3.267669768362701e-05,
932
+ "loss": 2.2027,
933
+ "step": 17500
934
+ },
935
+ {
936
+ "epoch": 3.56,
937
+ "learning_rate": 3.218174618887349e-05,
938
+ "loss": 2.2065,
939
+ "step": 18000
940
+ },
941
+ {
942
+ "epoch": 3.56,
943
+ "eval_COMMENT": {
944
+ "f1": 0.715327462850853,
945
+ "number": 6854,
946
+ "precision": 0.6767768810205675,
947
+ "recall": 0.7585351619492268
948
+ },
949
+ "eval_NAME": {
950
+ "f1": 0.8111738148984199,
951
+ "number": 8845,
952
+ "precision": 0.8098028169014084,
953
+ "recall": 0.8125494629734313
954
+ },
955
+ "eval_QTY": {
956
+ "f1": 0.9852766729467587,
957
+ "number": 7152,
958
+ "precision": 0.9834238751915308,
959
+ "recall": 0.9871364653243848
960
+ },
961
+ "eval_RANGE_END": {
962
+ "f1": 0.751937984496124,
963
+ "number": 105,
964
+ "precision": 0.6339869281045751,
965
+ "recall": 0.9238095238095239
966
+ },
967
+ "eval_UNIT": {
968
+ "f1": 0.9542920847268673,
969
+ "number": 5646,
970
+ "precision": 0.9250207813798836,
971
+ "recall": 0.9854764434998229
972
+ },
973
+ "eval_loss": 2.3392648696899414,
974
+ "eval_overall_accuracy": 0.829154319580579,
975
+ "eval_overall_f1": 0.8582709465695826,
976
+ "eval_overall_precision": 0.8395866773675762,
977
+ "eval_overall_recall": 0.8778057478498007,
978
+ "eval_runtime": 10.643,
979
+ "eval_samples_per_second": 799.209,
980
+ "eval_steps_per_second": 24.993,
981
+ "step": 18000
982
+ },
983
+ {
984
+ "epoch": 3.66,
985
+ "learning_rate": 3.168679469411997e-05,
986
+ "loss": 2.17,
987
+ "step": 18500
988
+ },
989
+ {
990
+ "epoch": 3.76,
991
+ "learning_rate": 3.119184319936647e-05,
992
+ "loss": 2.1758,
993
+ "step": 19000
994
+ },
995
+ {
996
+ "epoch": 3.76,
997
+ "eval_COMMENT": {
998
+ "f1": 0.7196268093572066,
999
+ "number": 6854,
1000
+ "precision": 0.6791402304803833,
1001
+ "recall": 0.7652465713451999
1002
+ },
1003
+ "eval_NAME": {
1004
+ "f1": 0.8154011420817548,
1005
+ "number": 8845,
1006
+ "precision": 0.8155394707079846,
1007
+ "recall": 0.8152628603730921
1008
+ },
1009
+ "eval_QTY": {
1010
+ "f1": 0.9850017439832579,
1011
+ "number": 7152,
1012
+ "precision": 0.9828762355561743,
1013
+ "recall": 0.9871364653243848
1014
+ },
1015
+ "eval_RANGE_END": {
1016
+ "f1": 0.7637795275590552,
1017
+ "number": 105,
1018
+ "precision": 0.6510067114093959,
1019
+ "recall": 0.9238095238095239
1020
+ },
1021
+ "eval_UNIT": {
1022
+ "f1": 0.9544714052988081,
1023
+ "number": 5646,
1024
+ "precision": 0.9250457038391224,
1025
+ "recall": 0.9858306765851931
1026
+ },
1027
+ "eval_loss": 2.306312322616577,
1028
+ "eval_overall_accuracy": 0.827710660284173,
1029
+ "eval_overall_f1": 0.8605851391072529,
1030
+ "eval_overall_precision": 0.8417129103429832,
1031
+ "eval_overall_recall": 0.8803230543318649,
1032
+ "eval_runtime": 11.977,
1033
+ "eval_samples_per_second": 710.192,
1034
+ "eval_steps_per_second": 22.209,
1035
+ "step": 19000
1036
+ },
1037
+ {
1038
+ "epoch": 3.86,
1039
+ "learning_rate": 3.069689170461295e-05,
1040
+ "loss": 2.2238,
1041
+ "step": 19500
1042
+ },
1043
+ {
1044
+ "epoch": 3.96,
1045
+ "learning_rate": 3.0201940209859435e-05,
1046
+ "loss": 2.1417,
1047
+ "step": 20000
1048
+ },
1049
+ {
1050
+ "epoch": 3.96,
1051
+ "eval_COMMENT": {
1052
+ "f1": 0.7152720243026789,
1053
+ "number": 6854,
1054
+ "precision": 0.6788990825688074,
1055
+ "recall": 0.7557630580682813
1056
+ },
1057
+ "eval_NAME": {
1058
+ "f1": 0.815481242573417,
1059
+ "number": 8845,
1060
+ "precision": 0.8162664250113276,
1061
+ "recall": 0.8146975692481628
1062
+ },
1063
+ "eval_QTY": {
1064
+ "f1": 0.9854263998326477,
1065
+ "number": 7152,
1066
+ "precision": 0.9828905271943247,
1067
+ "recall": 0.9879753914988815
1068
+ },
1069
+ "eval_RANGE_END": {
1070
+ "f1": 0.7634854771784232,
1071
+ "number": 105,
1072
+ "precision": 0.6764705882352942,
1073
+ "recall": 0.8761904761904762
1074
+ },
1075
+ "eval_UNIT": {
1076
+ "f1": 0.9533384893013664,
1077
+ "number": 5646,
1078
+ "precision": 0.9258888332498748,
1079
+ "recall": 0.9824654622741764
1080
+ },
1081
+ "eval_loss": 2.288215398788452,
1082
+ "eval_overall_accuracy": 0.8285084720006078,
1083
+ "eval_overall_f1": 0.8596340962039195,
1084
+ "eval_overall_precision": 0.8427151205749983,
1085
+ "eval_overall_recall": 0.877246346409342,
1086
+ "eval_runtime": 9.5122,
1087
+ "eval_samples_per_second": 894.221,
1088
+ "eval_steps_per_second": 27.964,
1089
+ "step": 20000
1090
+ },
1091
+ {
1092
+ "epoch": 4.06,
1093
+ "learning_rate": 2.970698871510592e-05,
1094
+ "loss": 2.1114,
1095
+ "step": 20500
1096
+ },
1097
+ {
1098
+ "epoch": 4.16,
1099
+ "learning_rate": 2.9212037220352405e-05,
1100
+ "loss": 2.0271,
1101
+ "step": 21000
1102
+ },
1103
+ {
1104
+ "epoch": 4.16,
1105
+ "eval_COMMENT": {
1106
+ "f1": 0.7168075752451809,
1107
+ "number": 6854,
1108
+ "precision": 0.6681376875551632,
1109
+ "recall": 0.7731251823752553
1110
+ },
1111
+ "eval_NAME": {
1112
+ "f1": 0.8170380818053596,
1113
+ "number": 8845,
1114
+ "precision": 0.815427927927928,
1115
+ "recall": 0.8186546071226681
1116
+ },
1117
+ "eval_QTY": {
1118
+ "f1": 0.9858546442756603,
1119
+ "number": 7152,
1120
+ "precision": 0.9826364772885123,
1121
+ "recall": 0.9890939597315436
1122
+ },
1123
+ "eval_RANGE_END": {
1124
+ "f1": 0.7717842323651452,
1125
+ "number": 105,
1126
+ "precision": 0.6838235294117647,
1127
+ "recall": 0.8857142857142857
1128
+ },
1129
+ "eval_UNIT": {
1130
+ "f1": 0.9534565366187543,
1131
+ "number": 5646,
1132
+ "precision": 0.922211188348229,
1133
+ "recall": 0.9868933758413035
1134
+ },
1135
+ "eval_loss": 2.350003242492676,
1136
+ "eval_overall_accuracy": 0.82989514474584,
1137
+ "eval_overall_f1": 0.859976186426263,
1138
+ "eval_overall_precision": 0.837385716178614,
1139
+ "eval_overall_recall": 0.8838193133347318,
1140
+ "eval_runtime": 11.0178,
1141
+ "eval_samples_per_second": 772.02,
1142
+ "eval_steps_per_second": 24.143,
1143
+ "step": 21000
1144
+ },
1145
+ {
1146
+ "epoch": 4.26,
1147
+ "learning_rate": 2.871708572559889e-05,
1148
+ "loss": 2.0589,
1149
+ "step": 21500
1150
+ },
1151
+ {
1152
+ "epoch": 4.36,
1153
+ "learning_rate": 2.8222134230845377e-05,
1154
+ "loss": 2.0488,
1155
+ "step": 22000
1156
+ },
1157
+ {
1158
+ "epoch": 4.36,
1159
+ "eval_COMMENT": {
1160
+ "f1": 0.7173793103448276,
1161
+ "number": 6854,
1162
+ "precision": 0.6802249542244311,
1163
+ "recall": 0.7588269623577473
1164
+ },
1165
+ "eval_NAME": {
1166
+ "f1": 0.814222122048797,
1167
+ "number": 8845,
1168
+ "precision": 0.8116153673331835,
1169
+ "recall": 0.8168456755228943
1170
+ },
1171
+ "eval_QTY": {
1172
+ "f1": 0.9854284319877291,
1173
+ "number": 7152,
1174
+ "precision": 0.9827562230565985,
1175
+ "recall": 0.9881152125279642
1176
+ },
1177
+ "eval_RANGE_END": {
1178
+ "f1": 0.7686274509803921,
1179
+ "number": 105,
1180
+ "precision": 0.6533333333333333,
1181
+ "recall": 0.9333333333333333
1182
+ },
1183
+ "eval_UNIT": {
1184
+ "f1": 0.9529190207156308,
1185
+ "number": 5646,
1186
+ "precision": 0.9221338634857521,
1187
+ "recall": 0.9858306765851931
1188
+ },
1189
+ "eval_loss": 2.2779643535614014,
1190
+ "eval_overall_accuracy": 0.8274067320112454,
1191
+ "eval_overall_f1": 0.8596716045585798,
1192
+ "eval_overall_precision": 0.8406683375104428,
1193
+ "eval_overall_recall": 0.8795538773512341,
1194
+ "eval_runtime": 10.9882,
1195
+ "eval_samples_per_second": 774.104,
1196
+ "eval_steps_per_second": 24.208,
1197
+ "step": 22000
1198
+ },
1199
+ {
1200
+ "epoch": 4.45,
1201
+ "learning_rate": 2.7727182736091867e-05,
1202
+ "loss": 2.0377,
1203
+ "step": 22500
1204
+ },
1205
+ {
1206
+ "epoch": 4.55,
1207
+ "learning_rate": 2.7232231241338353e-05,
1208
+ "loss": 2.0403,
1209
+ "step": 23000
1210
+ },
1211
+ {
1212
+ "epoch": 4.55,
1213
+ "eval_COMMENT": {
1214
+ "f1": 0.7213069552629764,
1215
+ "number": 6854,
1216
+ "precision": 0.6836534692277538,
1217
+ "recall": 0.7633498686898161
1218
+ },
1219
+ "eval_NAME": {
1220
+ "f1": 0.8175446529504862,
1221
+ "number": 8845,
1222
+ "precision": 0.8174522436984288,
1223
+ "recall": 0.8176370830977954
1224
+ },
1225
+ "eval_QTY": {
1226
+ "f1": 0.9858447806986962,
1227
+ "number": 7152,
1228
+ "precision": 0.9833078314090973,
1229
+ "recall": 0.9883948545861297
1230
+ },
1231
+ "eval_RANGE_END": {
1232
+ "f1": 0.7868852459016393,
1233
+ "number": 105,
1234
+ "precision": 0.6906474820143885,
1235
+ "recall": 0.9142857142857143
1236
+ },
1237
+ "eval_UNIT": {
1238
+ "f1": 0.9541991267870901,
1239
+ "number": 5646,
1240
+ "precision": 0.9234465617232809,
1241
+ "recall": 0.9870704923839887
1242
+ },
1243
+ "eval_loss": 2.255697250366211,
1244
+ "eval_overall_accuracy": 0.8292303016488108,
1245
+ "eval_overall_f1": 0.8621226374754127,
1246
+ "eval_overall_precision": 0.8439205706057663,
1247
+ "eval_overall_recall": 0.8811271939025243,
1248
+ "eval_runtime": 11.1445,
1249
+ "eval_samples_per_second": 763.249,
1250
+ "eval_steps_per_second": 23.868,
1251
+ "step": 23000
1252
+ },
1253
+ {
1254
+ "epoch": 4.65,
1255
+ "learning_rate": 2.6737279746584836e-05,
1256
+ "loss": 2.0887,
1257
+ "step": 23500
1258
+ },
1259
+ {
1260
+ "epoch": 4.75,
1261
+ "learning_rate": 2.6242328251831323e-05,
1262
+ "loss": 2.0443,
1263
+ "step": 24000
1264
+ },
1265
+ {
1266
+ "epoch": 4.75,
1267
+ "eval_COMMENT": {
1268
+ "f1": 0.7226055754899255,
1269
+ "number": 6854,
1270
+ "precision": 0.6855197695731867,
1271
+ "recall": 0.7639334695068573
1272
+ },
1273
+ "eval_NAME": {
1274
+ "f1": 0.8165780843605112,
1275
+ "number": 8845,
1276
+ "precision": 0.8167628096369189,
1277
+ "recall": 0.8163934426229508
1278
+ },
1279
+ "eval_QTY": {
1280
+ "f1": 0.9852161785216179,
1281
+ "number": 7152,
1282
+ "precision": 0.9827490261547023,
1283
+ "recall": 0.9876957494407159
1284
+ },
1285
+ "eval_RANGE_END": {
1286
+ "f1": 0.7854251012145749,
1287
+ "number": 105,
1288
+ "precision": 0.6830985915492958,
1289
+ "recall": 0.9238095238095239
1290
+ },
1291
+ "eval_UNIT": {
1292
+ "f1": 0.9537354352296092,
1293
+ "number": 5646,
1294
+ "precision": 0.9236641221374046,
1295
+ "recall": 0.9858306765851931
1296
+ },
1297
+ "eval_loss": 2.228408098220825,
1298
+ "eval_overall_accuracy": 0.829097333029405,
1299
+ "eval_overall_f1": 0.8619196741790305,
1300
+ "eval_overall_precision": 0.8441092676386794,
1301
+ "eval_overall_recall": 0.8804978672820083,
1302
+ "eval_runtime": 10.5005,
1303
+ "eval_samples_per_second": 810.058,
1304
+ "eval_steps_per_second": 25.332,
1305
+ "step": 24000
1306
+ },
1307
+ {
1308
+ "epoch": 4.85,
1309
+ "learning_rate": 2.5747376757077806e-05,
1310
+ "loss": 2.068,
1311
+ "step": 24500
1312
+ },
1313
+ {
1314
+ "epoch": 4.95,
1315
+ "learning_rate": 2.5252425262324292e-05,
1316
+ "loss": 2.0214,
1317
+ "step": 25000
1318
+ },
1319
+ {
1320
+ "epoch": 4.95,
1321
+ "eval_COMMENT": {
1322
+ "f1": 0.7221103783408538,
1323
+ "number": 6854,
1324
+ "precision": 0.6887829426566018,
1325
+ "recall": 0.7588269623577473
1326
+ },
1327
+ "eval_NAME": {
1328
+ "f1": 0.8139863300005649,
1329
+ "number": 8845,
1330
+ "precision": 0.8133890268683676,
1331
+ "recall": 0.814584511023177
1332
+ },
1333
+ "eval_QTY": {
1334
+ "f1": 0.9864751812604574,
1335
+ "number": 7152,
1336
+ "precision": 0.9837319243604005,
1337
+ "recall": 0.9892337807606264
1338
+ },
1339
+ "eval_RANGE_END": {
1340
+ "f1": 0.7713004484304932,
1341
+ "number": 105,
1342
+ "precision": 0.7288135593220338,
1343
+ "recall": 0.819047619047619
1344
+ },
1345
+ "eval_UNIT": {
1346
+ "f1": 0.9553288176283975,
1347
+ "number": 5646,
1348
+ "precision": 0.9258766827322586,
1349
+ "recall": 0.9867162592986185
1350
+ },
1351
+ "eval_loss": 2.2036967277526855,
1352
+ "eval_overall_accuracy": 0.8304270192234633,
1353
+ "eval_overall_f1": 0.8618053412869828,
1354
+ "eval_overall_precision": 0.8453726123217649,
1355
+ "eval_overall_recall": 0.8788895881406895,
1356
+ "eval_runtime": 10.7118,
1357
+ "eval_samples_per_second": 794.075,
1358
+ "eval_steps_per_second": 24.832,
1359
+ "step": 25000
1360
+ },
1361
+ {
1362
+ "epoch": 5.05,
1363
+ "learning_rate": 2.4757473767570778e-05,
1364
+ "loss": 2.0164,
1365
+ "step": 25500
1366
+ },
1367
+ {
1368
+ "epoch": 5.15,
1369
+ "learning_rate": 2.4262522272817265e-05,
1370
+ "loss": 2.0081,
1371
+ "step": 26000
1372
+ },
1373
+ {
1374
+ "epoch": 5.15,
1375
+ "eval_COMMENT": {
1376
+ "f1": 0.719671201814059,
1377
+ "number": 6854,
1378
+ "precision": 0.6996417745935519,
1379
+ "recall": 0.7408812372337321
1380
+ },
1381
+ "eval_NAME": {
1382
+ "f1": 0.8098846414838272,
1383
+ "number": 8845,
1384
+ "precision": 0.8101595203077271,
1385
+ "recall": 0.8096099491237988
1386
+ },
1387
+ "eval_QTY": {
1388
+ "f1": 0.9862001672706997,
1389
+ "number": 7152,
1390
+ "precision": 0.9831851028349082,
1391
+ "recall": 0.9892337807606264
1392
+ },
1393
+ "eval_RANGE_END": {
1394
+ "f1": 0.7918367346938776,
1395
+ "number": 105,
1396
+ "precision": 0.6928571428571428,
1397
+ "recall": 0.9238095238095239
1398
+ },
1399
+ "eval_UNIT": {
1400
+ "f1": 0.9546235819869371,
1401
+ "number": 5646,
1402
+ "precision": 0.927212020033389,
1403
+ "recall": 0.983705278072972
1404
+ },
1405
+ "eval_loss": 2.2013936042785645,
1406
+ "eval_overall_accuracy": 0.8273117544259555,
1407
+ "eval_overall_f1": 0.8604911676001723,
1408
+ "eval_overall_precision": 0.8484858783944533,
1409
+ "eval_overall_recall": 0.8728410600657297,
1410
+ "eval_runtime": 11.2303,
1411
+ "eval_samples_per_second": 757.413,
1412
+ "eval_steps_per_second": 23.686,
1413
+ "step": 26000
1414
+ },
1415
+ {
1416
+ "epoch": 5.25,
1417
+ "learning_rate": 2.376757077806375e-05,
1418
+ "loss": 1.9905,
1419
+ "step": 26500
1420
+ },
1421
+ {
1422
+ "epoch": 5.35,
1423
+ "learning_rate": 2.3272619283310237e-05,
1424
+ "loss": 1.9138,
1425
+ "step": 27000
1426
+ },
1427
+ {
1428
+ "epoch": 5.35,
1429
+ "eval_COMMENT": {
1430
+ "f1": 0.7232730263157895,
1431
+ "number": 6854,
1432
+ "precision": 0.6819591625743086,
1433
+ "recall": 0.7699153778815291
1434
+ },
1435
+ "eval_NAME": {
1436
+ "f1": 0.8175660419959357,
1437
+ "number": 8845,
1438
+ "precision": 0.8163679404802164,
1439
+ "recall": 0.818767665347654
1440
+ },
1441
+ "eval_QTY": {
1442
+ "f1": 0.9861333704968295,
1443
+ "number": 7152,
1444
+ "precision": 0.9829142936518961,
1445
+ "recall": 0.9893736017897091
1446
+ },
1447
+ "eval_RANGE_END": {
1448
+ "f1": 0.7679324894514767,
1449
+ "number": 105,
1450
+ "precision": 0.6893939393939394,
1451
+ "recall": 0.8666666666666667
1452
+ },
1453
+ "eval_UNIT": {
1454
+ "f1": 0.9538567493112948,
1455
+ "number": 5646,
1456
+ "precision": 0.9279731993299832,
1457
+ "recall": 0.9812256464753808
1458
+ },
1459
+ "eval_loss": 2.1838574409484863,
1460
+ "eval_overall_accuracy": 0.8322695843780867,
1461
+ "eval_overall_f1": 0.8622504785343178,
1462
+ "eval_overall_precision": 0.8433968572383818,
1463
+ "eval_overall_recall": 0.8819662960632124,
1464
+ "eval_runtime": 10.2972,
1465
+ "eval_samples_per_second": 826.053,
1466
+ "eval_steps_per_second": 25.832,
1467
+ "step": 27000
1468
+ },
1469
+ {
1470
+ "epoch": 5.44,
1471
+ "learning_rate": 2.2777667788556724e-05,
1472
+ "loss": 1.9236,
1473
+ "step": 27500
1474
+ },
1475
+ {
1476
+ "epoch": 5.54,
1477
+ "learning_rate": 2.2282716293803206e-05,
1478
+ "loss": 1.9304,
1479
+ "step": 28000
1480
+ },
1481
+ {
1482
+ "epoch": 5.54,
1483
+ "eval_COMMENT": {
1484
+ "f1": 0.7215675336447948,
1485
+ "number": 6854,
1486
+ "precision": 0.6910645118204889,
1487
+ "recall": 0.7548876568427196
1488
+ },
1489
+ "eval_NAME": {
1490
+ "f1": 0.8127016471387332,
1491
+ "number": 8845,
1492
+ "precision": 0.8137610519156654,
1493
+ "recall": 0.8116449971735443
1494
+ },
1495
+ "eval_QTY": {
1496
+ "f1": 0.9857760423929716,
1497
+ "number": 7152,
1498
+ "precision": 0.9831710709318497,
1499
+ "recall": 0.9883948545861297
1500
+ },
1501
+ "eval_RANGE_END": {
1502
+ "f1": 0.776,
1503
+ "number": 105,
1504
+ "precision": 0.6689655172413793,
1505
+ "recall": 0.9238095238095239
1506
+ },
1507
+ "eval_UNIT": {
1508
+ "f1": 0.9539864109400533,
1509
+ "number": 5646,
1510
+ "precision": 0.9272696873432537,
1511
+ "recall": 0.9822883457314914
1512
+ },
1513
+ "eval_loss": 2.1557235717773438,
1514
+ "eval_overall_accuracy": 0.8287364182053035,
1515
+ "eval_overall_f1": 0.860940800659488,
1516
+ "eval_overall_precision": 0.8460759493670886,
1517
+ "eval_overall_recall": 0.8763373190685966,
1518
+ "eval_runtime": 11.4111,
1519
+ "eval_samples_per_second": 745.412,
1520
+ "eval_steps_per_second": 23.311,
1521
+ "step": 28000
1522
+ },
1523
+ {
1524
+ "epoch": 5.64,
1525
+ "learning_rate": 2.1787764799049696e-05,
1526
+ "loss": 1.908,
1527
+ "step": 28500
1528
+ },
1529
+ {
1530
+ "epoch": 5.74,
1531
+ "learning_rate": 2.129281330429618e-05,
1532
+ "loss": 1.9369,
1533
+ "step": 29000
1534
+ },
1535
+ {
1536
+ "epoch": 5.74,
1537
+ "eval_COMMENT": {
1538
+ "f1": 0.7214330697641872,
1539
+ "number": 6854,
1540
+ "precision": 0.6931558424095737,
1541
+ "recall": 0.7521155529617741
1542
+ },
1543
+ "eval_NAME": {
1544
+ "f1": 0.8120292235374073,
1545
+ "number": 8845,
1546
+ "precision": 0.8135497049477984,
1547
+ "recall": 0.8105144149236857
1548
+ },
1549
+ "eval_QTY": {
1550
+ "f1": 0.9862020905923344,
1551
+ "number": 7152,
1552
+ "precision": 0.9830508474576272,
1553
+ "recall": 0.9893736017897091
1554
+ },
1555
+ "eval_RANGE_END": {
1556
+ "f1": 0.7841409691629957,
1557
+ "number": 105,
1558
+ "precision": 0.7295081967213115,
1559
+ "recall": 0.8476190476190476
1560
+ },
1561
+ "eval_UNIT": {
1562
+ "f1": 0.9530419880034275,
1563
+ "number": 5646,
1564
+ "precision": 0.923140770252324,
1565
+ "recall": 0.9849450938717677
1566
+ },
1567
+ "eval_loss": 2.152221918106079,
1568
+ "eval_overall_accuracy": 0.8286794316541296,
1569
+ "eval_overall_f1": 0.8608987026376836,
1570
+ "eval_overall_precision": 0.8464839658027237,
1571
+ "eval_overall_recall": 0.8758128802181666,
1572
+ "eval_runtime": 8.8394,
1573
+ "eval_samples_per_second": 962.281,
1574
+ "eval_steps_per_second": 30.093,
1575
+ "step": 29000
1576
+ },
1577
+ {
1578
+ "epoch": 5.84,
1579
+ "learning_rate": 2.0797861809542665e-05,
1580
+ "loss": 1.9176,
1581
+ "step": 29500
1582
+ },
1583
+ {
1584
+ "epoch": 5.94,
1585
+ "learning_rate": 2.0302910314789152e-05,
1586
+ "loss": 1.8944,
1587
+ "step": 30000
1588
+ },
1589
+ {
1590
+ "epoch": 5.94,
1591
+ "eval_COMMENT": {
1592
+ "f1": 0.723598615916955,
1593
+ "number": 6854,
1594
+ "precision": 0.6882569773565034,
1595
+ "recall": 0.762766267872775
1596
+ },
1597
+ "eval_NAME": {
1598
+ "f1": 0.8156853881794554,
1599
+ "number": 8845,
1600
+ "precision": 0.8153168417485598,
1601
+ "recall": 0.8160542679479932
1602
+ },
1603
+ "eval_QTY": {
1604
+ "f1": 0.9857272157627236,
1605
+ "number": 7152,
1606
+ "precision": 0.9816946331992789,
1607
+ "recall": 0.9897930648769575
1608
+ },
1609
+ "eval_RANGE_END": {
1610
+ "f1": 0.7631578947368421,
1611
+ "number": 105,
1612
+ "precision": 0.7073170731707317,
1613
+ "recall": 0.8285714285714286
1614
+ },
1615
+ "eval_UNIT": {
1616
+ "f1": 0.9549935705100728,
1617
+ "number": 5646,
1618
+ "precision": 0.9254028908456554,
1619
+ "recall": 0.9865391427559334
1620
+ },
1621
+ "eval_loss": 2.128391742706299,
1622
+ "eval_overall_accuracy": 0.8317377099004635,
1623
+ "eval_overall_f1": 0.8623381960139715,
1624
+ "eval_overall_precision": 0.8449768471914637,
1625
+ "eval_overall_recall": 0.880427942101951,
1626
+ "eval_runtime": 11.5016,
1627
+ "eval_samples_per_second": 739.547,
1628
+ "eval_steps_per_second": 23.127,
1629
+ "step": 30000
1630
+ },
1631
+ {
1632
+ "epoch": 6.04,
1633
+ "learning_rate": 1.9807958820035638e-05,
1634
+ "loss": 1.837,
1635
+ "step": 30500
1636
+ },
1637
+ {
1638
+ "epoch": 6.14,
1639
+ "learning_rate": 1.9313007325282124e-05,
1640
+ "loss": 1.8311,
1641
+ "step": 31000
1642
+ },
1643
+ {
1644
+ "epoch": 6.14,
1645
+ "eval_COMMENT": {
1646
+ "f1": 0.7244426318651441,
1647
+ "number": 6854,
1648
+ "precision": 0.6781623822855688,
1649
+ "recall": 0.7775021885030639
1650
+ },
1651
+ "eval_NAME": {
1652
+ "f1": 0.818961625282167,
1653
+ "number": 8845,
1654
+ "precision": 0.8175774647887324,
1655
+ "recall": 0.8203504804974562
1656
+ },
1657
+ "eval_QTY": {
1658
+ "f1": 0.9856425982715361,
1659
+ "number": 7152,
1660
+ "precision": 0.9826292384658143,
1661
+ "recall": 0.9886744966442953
1662
+ },
1663
+ "eval_RANGE_END": {
1664
+ "f1": 0.7896995708154506,
1665
+ "number": 105,
1666
+ "precision": 0.71875,
1667
+ "recall": 0.8761904761904762
1668
+ },
1669
+ "eval_UNIT": {
1670
+ "f1": 0.9552008238928938,
1671
+ "number": 5646,
1672
+ "precision": 0.9265734265734266,
1673
+ "recall": 0.9856535600425079
1674
+ },
1675
+ "eval_loss": 2.171062469482422,
1676
+ "eval_overall_accuracy": 0.8314527771445939,
1677
+ "eval_overall_f1": 0.8629676979459644,
1678
+ "eval_overall_precision": 0.8419984698799189,
1679
+ "eval_overall_recall": 0.8850080413957065,
1680
+ "eval_runtime": 11.2938,
1681
+ "eval_samples_per_second": 753.154,
1682
+ "eval_steps_per_second": 23.553,
1683
+ "step": 31000
1684
+ },
1685
+ {
1686
+ "epoch": 6.24,
1687
+ "learning_rate": 1.8818055830528607e-05,
1688
+ "loss": 1.8426,
1689
+ "step": 31500
1690
+ },
1691
+ {
1692
+ "epoch": 6.34,
1693
+ "learning_rate": 1.8323104335775097e-05,
1694
+ "loss": 1.879,
1695
+ "step": 32000
1696
+ },
1697
+ {
1698
+ "epoch": 6.34,
1699
+ "eval_COMMENT": {
1700
+ "f1": 0.7243460764587525,
1701
+ "number": 6854,
1702
+ "precision": 0.6905675353882789,
1703
+ "recall": 0.7615990662386928
1704
+ },
1705
+ "eval_NAME": {
1706
+ "f1": 0.8148399502318742,
1707
+ "number": 8845,
1708
+ "precision": 0.8152087812606088,
1709
+ "recall": 0.8144714527981911
1710
+ },
1711
+ "eval_QTY": {
1712
+ "f1": 0.985952712100139,
1713
+ "number": 7152,
1714
+ "precision": 0.9807692307692307,
1715
+ "recall": 0.9911912751677853
1716
+ },
1717
+ "eval_RANGE_END": {
1718
+ "f1": 0.7796610169491526,
1719
+ "number": 105,
1720
+ "precision": 0.7022900763358778,
1721
+ "recall": 0.8761904761904762
1722
+ },
1723
+ "eval_UNIT": {
1724
+ "f1": 0.9541174456428694,
1725
+ "number": 5646,
1726
+ "precision": 0.9232935719019219,
1727
+ "recall": 0.9870704923839887
1728
+ },
1729
+ "eval_loss": 2.1472506523132324,
1730
+ "eval_overall_accuracy": 0.830635969911101,
1731
+ "eval_overall_f1": 0.8623636394773346,
1732
+ "eval_overall_precision": 0.8451545768856366,
1733
+ "eval_overall_recall": 0.8802880917418362,
1734
+ "eval_runtime": 12.4001,
1735
+ "eval_samples_per_second": 685.964,
1736
+ "eval_steps_per_second": 21.452,
1737
+ "step": 32000
1738
+ },
1739
+ {
1740
+ "epoch": 6.43,
1741
+ "learning_rate": 1.782815284102158e-05,
1742
+ "loss": 1.8605,
1743
+ "step": 32500
1744
+ },
1745
+ {
1746
+ "epoch": 6.53,
1747
+ "learning_rate": 1.7333201346268066e-05,
1748
+ "loss": 1.8279,
1749
+ "step": 33000
1750
+ },
1751
+ {
1752
+ "epoch": 6.53,
1753
+ "eval_COMMENT": {
1754
+ "f1": 0.7266004792879152,
1755
+ "number": 6854,
1756
+ "precision": 0.6845568313765966,
1757
+ "recall": 0.7741464838050773
1758
+ },
1759
+ "eval_NAME": {
1760
+ "f1": 0.8171618650279078,
1761
+ "number": 8845,
1762
+ "precision": 0.8150022492127755,
1763
+ "recall": 0.8193329564725834
1764
+ },
1765
+ "eval_QTY": {
1766
+ "f1": 0.9857839721254356,
1767
+ "number": 7152,
1768
+ "precision": 0.9826340650180606,
1769
+ "recall": 0.9889541387024608
1770
+ },
1771
+ "eval_RANGE_END": {
1772
+ "f1": 0.7860262008733625,
1773
+ "number": 105,
1774
+ "precision": 0.7258064516129032,
1775
+ "recall": 0.8571428571428571
1776
+ },
1777
+ "eval_UNIT": {
1778
+ "f1": 0.9554850330216998,
1779
+ "number": 5646,
1780
+ "precision": 0.9263262930317645,
1781
+ "recall": 0.9865391427559334
1782
+ },
1783
+ "eval_loss": 2.1636247634887695,
1784
+ "eval_overall_accuracy": 0.83139579059342,
1785
+ "eval_overall_f1": 0.8632980539433255,
1786
+ "eval_overall_precision": 0.8434852224964974,
1787
+ "eval_overall_recall": 0.8840640514649325,
1788
+ "eval_runtime": 11.6243,
1789
+ "eval_samples_per_second": 731.745,
1790
+ "eval_steps_per_second": 22.883,
1791
+ "step": 33000
1792
+ },
1793
+ {
1794
+ "epoch": 6.63,
1795
+ "learning_rate": 1.6838249851514553e-05,
1796
+ "loss": 1.8596,
1797
+ "step": 33500
1798
+ },
1799
+ {
1800
+ "epoch": 6.73,
1801
+ "learning_rate": 1.634329835676104e-05,
1802
+ "loss": 1.8613,
1803
+ "step": 34000
1804
+ },
1805
+ {
1806
+ "epoch": 6.73,
1807
+ "eval_COMMENT": {
1808
+ "f1": 0.7281226369698219,
1809
+ "number": 6854,
1810
+ "precision": 0.6884180423761861,
1811
+ "recall": 0.7726874817624745
1812
+ },
1813
+ "eval_NAME": {
1814
+ "f1": 0.8162550161080653,
1815
+ "number": 8845,
1816
+ "precision": 0.8161166365280289,
1817
+ "recall": 0.8163934426229508
1818
+ },
1819
+ "eval_QTY": {
1820
+ "f1": 0.9855233853006681,
1821
+ "number": 7152,
1822
+ "precision": 0.9811529933481153,
1823
+ "recall": 0.9899328859060402
1824
+ },
1825
+ "eval_RANGE_END": {
1826
+ "f1": 0.7777777777777778,
1827
+ "number": 105,
1828
+ "precision": 0.6666666666666666,
1829
+ "recall": 0.9333333333333333
1830
+ },
1831
+ "eval_UNIT": {
1832
+ "f1": 0.9550600343053174,
1833
+ "number": 5646,
1834
+ "precision": 0.9258397073495178,
1835
+ "recall": 0.9861849096705633
1836
+ },
1837
+ "eval_loss": 2.119246482849121,
1838
+ "eval_overall_accuracy": 0.8333523288503913,
1839
+ "eval_overall_f1": 0.8633971291866029,
1840
+ "eval_overall_precision": 0.8444080486663547,
1841
+ "eval_overall_recall": 0.8832599118942731,
1842
+ "eval_runtime": 9.0301,
1843
+ "eval_samples_per_second": 941.963,
1844
+ "eval_steps_per_second": 29.457,
1845
+ "step": 34000
1846
+ },
1847
+ {
1848
+ "epoch": 6.83,
1849
+ "learning_rate": 1.5848346862007525e-05,
1850
+ "loss": 1.8804,
1851
+ "step": 34500
1852
+ },
1853
+ {
1854
+ "epoch": 6.93,
1855
+ "learning_rate": 1.535339536725401e-05,
1856
+ "loss": 1.8604,
1857
+ "step": 35000
1858
+ },
1859
+ {
1860
+ "epoch": 6.93,
1861
+ "eval_COMMENT": {
1862
+ "f1": 0.7285265601529427,
1863
+ "number": 6854,
1864
+ "precision": 0.68467659137577,
1865
+ "recall": 0.7783775897286256
1866
+ },
1867
+ "eval_NAME": {
1868
+ "f1": 0.8183306055646481,
1869
+ "number": 8845,
1870
+ "precision": 0.8169934640522876,
1871
+ "recall": 0.819672131147541
1872
+ },
1873
+ "eval_QTY": {
1874
+ "f1": 0.9865589525732991,
1875
+ "number": 7152,
1876
+ "precision": 0.9827945053420286,
1877
+ "recall": 0.9903523489932886
1878
+ },
1879
+ "eval_RANGE_END": {
1880
+ "f1": 0.7818930041152263,
1881
+ "number": 105,
1882
+ "precision": 0.6884057971014492,
1883
+ "recall": 0.9047619047619048
1884
+ },
1885
+ "eval_UNIT": {
1886
+ "f1": 0.9555517418911963,
1887
+ "number": 5646,
1888
+ "precision": 0.9267643142476698,
1889
+ "recall": 0.9861849096705633
1890
+ },
1891
+ "eval_loss": 2.1069583892822266,
1892
+ "eval_overall_accuracy": 0.834340095737406,
1893
+ "eval_overall_f1": 0.8642295423141878,
1894
+ "eval_overall_precision": 0.8438322395815984,
1895
+ "eval_overall_recall": 0.8856373680162226,
1896
+ "eval_runtime": 11.4858,
1897
+ "eval_samples_per_second": 740.57,
1898
+ "eval_steps_per_second": 23.159,
1899
+ "step": 35000
1900
+ },
1901
+ {
1902
+ "epoch": 7.03,
1903
+ "learning_rate": 1.4858443872500496e-05,
1904
+ "loss": 1.7995,
1905
+ "step": 35500
1906
+ },
1907
+ {
1908
+ "epoch": 7.13,
1909
+ "learning_rate": 1.4363492377746981e-05,
1910
+ "loss": 1.8026,
1911
+ "step": 36000
1912
+ },
1913
+ {
1914
+ "epoch": 7.13,
1915
+ "eval_COMMENT": {
1916
+ "f1": 0.7254587315984092,
1917
+ "number": 6854,
1918
+ "precision": 0.695146409947854,
1919
+ "recall": 0.7585351619492268
1920
+ },
1921
+ "eval_NAME": {
1922
+ "f1": 0.8138180584610165,
1923
+ "number": 8845,
1924
+ "precision": 0.8139561185252205,
1925
+ "recall": 0.81368004522329
1926
+ },
1927
+ "eval_QTY": {
1928
+ "f1": 0.9861982434127978,
1929
+ "number": 7152,
1930
+ "precision": 0.9833194328607172,
1931
+ "recall": 0.9890939597315436
1932
+ },
1933
+ "eval_RANGE_END": {
1934
+ "f1": 0.7692307692307693,
1935
+ "number": 105,
1936
+ "precision": 0.6976744186046512,
1937
+ "recall": 0.8571428571428571
1938
+ },
1939
+ "eval_UNIT": {
1940
+ "f1": 0.9548265200961868,
1941
+ "number": 5646,
1942
+ "precision": 0.926808936312104,
1943
+ "recall": 0.9845908607863975
1944
+ },
1945
+ "eval_loss": 2.1282002925872803,
1946
+ "eval_overall_accuracy": 0.8295152344046804,
1947
+ "eval_overall_f1": 0.8625437813336996,
1948
+ "eval_overall_precision": 0.8474124552999123,
1949
+ "eval_overall_recall": 0.8782252989301448,
1950
+ "eval_runtime": 9.0618,
1951
+ "eval_samples_per_second": 938.668,
1952
+ "eval_steps_per_second": 29.354,
1953
+ "step": 36000
1954
+ },
1955
+ {
1956
+ "epoch": 7.23,
1957
+ "learning_rate": 1.3868540882993467e-05,
1958
+ "loss": 1.7692,
1959
+ "step": 36500
1960
+ },
1961
+ {
1962
+ "epoch": 7.33,
1963
+ "learning_rate": 1.3373589388239954e-05,
1964
+ "loss": 1.774,
1965
+ "step": 37000
1966
+ },
1967
+ {
1968
+ "epoch": 7.33,
1969
+ "eval_COMMENT": {
1970
+ "f1": 0.7252502780867629,
1971
+ "number": 6854,
1972
+ "precision": 0.6926958831341301,
1973
+ "recall": 0.7610154654216515
1974
+ },
1975
+ "eval_NAME": {
1976
+ "f1": 0.8135153429602889,
1977
+ "number": 8845,
1978
+ "precision": 0.8117753011370032,
1979
+ "recall": 0.8152628603730921
1980
+ },
1981
+ "eval_QTY": {
1982
+ "f1": 0.9858644941160087,
1983
+ "number": 7152,
1984
+ "precision": 0.9819669857123041,
1985
+ "recall": 0.9897930648769575
1986
+ },
1987
+ "eval_RANGE_END": {
1988
+ "f1": 0.7948717948717948,
1989
+ "number": 105,
1990
+ "precision": 0.7209302325581395,
1991
+ "recall": 0.8857142857142857
1992
+ },
1993
+ "eval_UNIT": {
1994
+ "f1": 0.953885787891799,
1995
+ "number": 5646,
1996
+ "precision": 0.9258209701616936,
1997
+ "recall": 0.983705278072972
1998
+ },
1999
+ "eval_loss": 2.1374754905700684,
2000
+ "eval_overall_accuracy": 0.829952131297014,
2001
+ "eval_overall_f1": 0.8621126953660542,
2002
+ "eval_overall_precision": 0.8454789915966386,
2003
+ "eval_overall_recall": 0.8794140269911195,
2004
+ "eval_runtime": 13.9271,
2005
+ "eval_samples_per_second": 610.751,
2006
+ "eval_steps_per_second": 19.099,
2007
+ "step": 37000
2008
+ },
2009
+ {
2010
+ "epoch": 7.42,
2011
+ "learning_rate": 1.287863789348644e-05,
2012
+ "loss": 1.7909,
2013
+ "step": 37500
2014
+ },
2015
+ {
2016
+ "epoch": 7.52,
2017
+ "learning_rate": 1.2383686398732925e-05,
2018
+ "loss": 1.8132,
2019
+ "step": 38000
2020
+ },
2021
+ {
2022
+ "epoch": 7.52,
2023
+ "eval_COMMENT": {
2024
+ "f1": 0.7251632624704737,
2025
+ "number": 6854,
2026
+ "precision": 0.6921750663129973,
2027
+ "recall": 0.7614531660344325
2028
+ },
2029
+ "eval_NAME": {
2030
+ "f1": 0.8144125798970531,
2031
+ "number": 8845,
2032
+ "precision": 0.8149196287072674,
2033
+ "recall": 0.8139061616732617
2034
+ },
2035
+ "eval_QTY": {
2036
+ "f1": 0.9862059356276995,
2037
+ "number": 7152,
2038
+ "precision": 0.9827825603998889,
2039
+ "recall": 0.9896532438478747
2040
+ },
2041
+ "eval_RANGE_END": {
2042
+ "f1": 0.7966804979253113,
2043
+ "number": 105,
2044
+ "precision": 0.7058823529411765,
2045
+ "recall": 0.9142857142857143
2046
+ },
2047
+ "eval_UNIT": {
2048
+ "f1": 0.9550012856775519,
2049
+ "number": 5646,
2050
+ "precision": 0.9252615844544095,
2051
+ "recall": 0.9867162592986185
2052
+ },
2053
+ "eval_loss": 2.1093838214874268,
2054
+ "eval_overall_accuracy": 0.8298571537117241,
2055
+ "eval_overall_f1": 0.8627067798062913,
2056
+ "eval_overall_precision": 0.8462987253220328,
2057
+ "eval_overall_recall": 0.8797636528914062,
2058
+ "eval_runtime": 10.2321,
2059
+ "eval_samples_per_second": 831.306,
2060
+ "eval_steps_per_second": 25.997,
2061
+ "step": 38000
2062
+ },
2063
+ {
2064
+ "epoch": 7.62,
2065
+ "learning_rate": 1.1888734903979411e-05,
2066
+ "loss": 1.7708,
2067
+ "step": 38500
2068
+ },
2069
+ {
2070
+ "epoch": 7.72,
2071
+ "learning_rate": 1.1393783409225896e-05,
2072
+ "loss": 1.805,
2073
+ "step": 39000
2074
+ },
2075
+ {
2076
+ "epoch": 7.72,
2077
+ "eval_COMMENT": {
2078
+ "f1": 0.7264215888751205,
2079
+ "number": 6854,
2080
+ "precision": 0.6876955161626694,
2081
+ "recall": 0.7697694776772688
2082
+ },
2083
+ "eval_NAME": {
2084
+ "f1": 0.815460358779922,
2085
+ "number": 8845,
2086
+ "precision": 0.8163380920009065,
2087
+ "recall": 0.814584511023177
2088
+ },
2089
+ "eval_QTY": {
2090
+ "f1": 0.9862822923194763,
2091
+ "number": 7152,
2092
+ "precision": 0.9823831321958663,
2093
+ "recall": 0.9902125279642058
2094
+ },
2095
+ "eval_RANGE_END": {
2096
+ "f1": 0.7844827586206896,
2097
+ "number": 105,
2098
+ "precision": 0.7165354330708661,
2099
+ "recall": 0.8666666666666667
2100
+ },
2101
+ "eval_UNIT": {
2102
+ "f1": 0.9549858526965618,
2103
+ "number": 5646,
2104
+ "precision": 0.9255442911750041,
2105
+ "recall": 0.9863620262132483
2106
+ },
2107
+ "eval_loss": 2.1103549003601074,
2108
+ "eval_overall_accuracy": 0.8331053871286377,
2109
+ "eval_overall_f1": 0.8630181513352608,
2110
+ "eval_overall_precision": 0.8449633178117986,
2111
+ "eval_overall_recall": 0.8818614082931263,
2112
+ "eval_runtime": 10.8182,
2113
+ "eval_samples_per_second": 786.27,
2114
+ "eval_steps_per_second": 24.588,
2115
+ "step": 39000
2116
+ },
2117
+ {
2118
+ "epoch": 7.82,
2119
+ "learning_rate": 1.0898831914472382e-05,
2120
+ "loss": 1.8185,
2121
+ "step": 39500
2122
+ },
2123
+ {
2124
+ "epoch": 7.92,
2125
+ "learning_rate": 1.0403880419718868e-05,
2126
+ "loss": 1.7337,
2127
+ "step": 40000
2128
+ },
2129
+ {
2130
+ "epoch": 7.92,
2131
+ "eval_COMMENT": {
2132
+ "f1": 0.7251437677544517,
2133
+ "number": 6854,
2134
+ "precision": 0.6904604829133131,
2135
+ "recall": 0.7634957688940764
2136
+ },
2137
+ "eval_NAME": {
2138
+ "f1": 0.8154846001695395,
2139
+ "number": 8845,
2140
+ "precision": 0.8152542372881356,
2141
+ "recall": 0.8157150932730356
2142
+ },
2143
+ "eval_QTY": {
2144
+ "f1": 0.9866220735785953,
2145
+ "number": 7152,
2146
+ "precision": 0.9833333333333333,
2147
+ "recall": 0.9899328859060402
2148
+ },
2149
+ "eval_RANGE_END": {
2150
+ "f1": 0.8,
2151
+ "number": 105,
2152
+ "precision": 0.7,
2153
+ "recall": 0.9333333333333333
2154
+ },
2155
+ "eval_UNIT": {
2156
+ "f1": 0.9544557852302942,
2157
+ "number": 5646,
2158
+ "precision": 0.9253284550141361,
2159
+ "recall": 0.9854764434998229
2160
+ },
2161
+ "eval_loss": 2.1034367084503174,
2162
+ "eval_overall_accuracy": 0.830616974394043,
2163
+ "eval_overall_f1": 0.8629076459303919,
2164
+ "eval_overall_precision": 0.8458129071251091,
2165
+ "eval_overall_recall": 0.8807076428221803,
2166
+ "eval_runtime": 10.7303,
2167
+ "eval_samples_per_second": 792.708,
2168
+ "eval_steps_per_second": 24.79,
2169
+ "step": 40000
2170
+ },
2171
+ {
2172
+ "epoch": 8.02,
2173
+ "learning_rate": 9.908928924965353e-06,
2174
+ "loss": 1.7519,
2175
+ "step": 40500
2176
+ },
2177
+ {
2178
+ "epoch": 8.12,
2179
+ "learning_rate": 9.41397743021184e-06,
2180
+ "loss": 1.7771,
2181
+ "step": 41000
2182
+ },
2183
+ {
2184
+ "epoch": 8.12,
2185
+ "eval_COMMENT": {
2186
+ "f1": 0.7258660347110893,
2187
+ "number": 6854,
2188
+ "precision": 0.6949152542372882,
2189
+ "recall": 0.759702363583309
2190
+ },
2191
+ "eval_NAME": {
2192
+ "f1": 0.8134750169568167,
2193
+ "number": 8845,
2194
+ "precision": 0.8133830677065672,
2195
+ "recall": 0.8135669869983041
2196
+ },
2197
+ "eval_QTY": {
2198
+ "f1": 0.9863395595204906,
2199
+ "number": 7152,
2200
+ "precision": 0.9833240689271817,
2201
+ "recall": 0.9893736017897091
2202
+ },
2203
+ "eval_RANGE_END": {
2204
+ "f1": 0.7931034482758621,
2205
+ "number": 105,
2206
+ "precision": 0.7244094488188977,
2207
+ "recall": 0.8761904761904762
2208
+ },
2209
+ "eval_UNIT": {
2210
+ "f1": 0.9552213149978513,
2211
+ "number": 5646,
2212
+ "precision": 0.9278677575555184,
2213
+ "recall": 0.9842366277010273
2214
+ },
2215
+ "eval_loss": 2.107405424118042,
2216
+ "eval_overall_accuracy": 0.8285654585517818,
2217
+ "eval_overall_f1": 0.8627047069729117,
2218
+ "eval_overall_precision": 0.8474301902063942,
2219
+ "eval_overall_recall": 0.8785399622404028,
2220
+ "eval_runtime": 11.3451,
2221
+ "eval_samples_per_second": 749.75,
2222
+ "eval_steps_per_second": 23.446,
2223
+ "step": 41000
2224
+ },
2225
+ {
2226
+ "epoch": 8.22,
2227
+ "learning_rate": 8.919025935458326e-06,
2228
+ "loss": 1.7381,
2229
+ "step": 41500
2230
+ },
2231
+ {
2232
+ "epoch": 8.32,
2233
+ "learning_rate": 8.424074440704812e-06,
2234
+ "loss": 1.7179,
2235
+ "step": 42000
2236
+ },
2237
+ {
2238
+ "epoch": 8.32,
2239
+ "eval_COMMENT": {
2240
+ "f1": 0.7297001232370259,
2241
+ "number": 6854,
2242
+ "precision": 0.6874355005159959,
2243
+ "recall": 0.7775021885030639
2244
+ },
2245
+ "eval_NAME": {
2246
+ "f1": 0.8157106527267589,
2247
+ "number": 8845,
2248
+ "precision": 0.8154802259887005,
2249
+ "recall": 0.8159412097230073
2250
+ },
2251
+ "eval_QTY": {
2252
+ "f1": 0.9864158829676071,
2253
+ "number": 7152,
2254
+ "precision": 0.982923781757601,
2255
+ "recall": 0.9899328859060402
2256
+ },
2257
+ "eval_RANGE_END": {
2258
+ "f1": 0.8016194331983806,
2259
+ "number": 105,
2260
+ "precision": 0.6971830985915493,
2261
+ "recall": 0.9428571428571428
2262
+ },
2263
+ "eval_UNIT": {
2264
+ "f1": 0.954233801851217,
2265
+ "number": 5646,
2266
+ "precision": 0.9244437064098306,
2267
+ "recall": 0.9860077931278781
2268
+ },
2269
+ "eval_loss": 2.1069343090057373,
2270
+ "eval_overall_accuracy": 0.8319276650710432,
2271
+ "eval_overall_f1": 0.86363558757747,
2272
+ "eval_overall_precision": 0.8439387366945844,
2273
+ "eval_overall_recall": 0.8842738270051045,
2274
+ "eval_runtime": 11.303,
2275
+ "eval_samples_per_second": 752.544,
2276
+ "eval_steps_per_second": 23.534,
2277
+ "step": 42000
2278
+ },
2279
+ {
2280
+ "epoch": 8.41,
2281
+ "learning_rate": 7.929122945951298e-06,
2282
+ "loss": 1.7763,
2283
+ "step": 42500
2284
+ },
2285
+ {
2286
+ "epoch": 8.51,
2287
+ "learning_rate": 7.434171451197783e-06,
2288
+ "loss": 1.7005,
2289
+ "step": 43000
2290
+ },
2291
+ {
2292
+ "epoch": 8.51,
2293
+ "eval_COMMENT": {
2294
+ "f1": 0.7259434619133825,
2295
+ "number": 6854,
2296
+ "precision": 0.694326052210975,
2297
+ "recall": 0.7605777648088707
2298
+ },
2299
+ "eval_NAME": {
2300
+ "f1": 0.8142243328810492,
2301
+ "number": 8845,
2302
+ "precision": 0.8143164084586678,
2303
+ "recall": 0.8141322781232334
2304
+ },
2305
+ "eval_QTY": {
2306
+ "f1": 0.9863471719141822,
2307
+ "number": 7152,
2308
+ "precision": 0.9827873403664631,
2309
+ "recall": 0.9899328859060402
2310
+ },
2311
+ "eval_RANGE_END": {
2312
+ "f1": 0.7894736842105263,
2313
+ "number": 105,
2314
+ "precision": 0.7317073170731707,
2315
+ "recall": 0.8571428571428571
2316
+ },
2317
+ "eval_UNIT": {
2318
+ "f1": 0.9534087016101404,
2319
+ "number": 5646,
2320
+ "precision": 0.9230514096185738,
2321
+ "recall": 0.9858306765851931
2322
+ },
2323
+ "eval_loss": 2.1151254177093506,
2324
+ "eval_overall_accuracy": 0.8293252792341007,
2325
+ "eval_overall_f1": 0.8626307665923513,
2326
+ "eval_overall_precision": 0.8465733135855662,
2327
+ "eval_overall_recall": 0.8793091392210335,
2328
+ "eval_runtime": 10.9284,
2329
+ "eval_samples_per_second": 778.339,
2330
+ "eval_steps_per_second": 24.34,
2331
+ "step": 43000
2332
+ },
2333
+ {
2334
+ "epoch": 8.61,
2335
+ "learning_rate": 6.939219956444269e-06,
2336
+ "loss": 1.7224,
2337
+ "step": 43500
2338
+ },
2339
+ {
2340
+ "epoch": 8.71,
2341
+ "learning_rate": 6.444268461690754e-06,
2342
+ "loss": 1.7078,
2343
+ "step": 44000
2344
+ },
2345
+ {
2346
+ "epoch": 8.71,
2347
+ "eval_COMMENT": {
2348
+ "f1": 0.7251940133037693,
2349
+ "number": 6854,
2350
+ "precision": 0.6905515967273687,
2351
+ "recall": 0.7634957688940764
2352
+ },
2353
+ "eval_NAME": {
2354
+ "f1": 0.8152167768922051,
2355
+ "number": 8845,
2356
+ "precision": 0.8151706986208456,
2357
+ "recall": 0.8152628603730921
2358
+ },
2359
+ "eval_QTY": {
2360
+ "f1": 0.9865495853369572,
2361
+ "number": 7152,
2362
+ "precision": 0.9834653327775462,
2363
+ "recall": 0.9896532438478747
2364
+ },
2365
+ "eval_RANGE_END": {
2366
+ "f1": 0.7899159663865547,
2367
+ "number": 105,
2368
+ "precision": 0.706766917293233,
2369
+ "recall": 0.8952380952380953
2370
+ },
2371
+ "eval_UNIT": {
2372
+ "f1": 0.9550831476084348,
2373
+ "number": 5646,
2374
+ "precision": 0.9254152823920265,
2375
+ "recall": 0.9867162592986185
2376
+ },
2377
+ "eval_loss": 2.1110451221466064,
2378
+ "eval_overall_accuracy": 0.8313008130081301,
2379
+ "eval_overall_f1": 0.8629231190900369,
2380
+ "eval_overall_precision": 0.8459394102236851,
2381
+ "eval_overall_recall": 0.8806027550520943,
2382
+ "eval_runtime": 11.2874,
2383
+ "eval_samples_per_second": 753.583,
2384
+ "eval_steps_per_second": 23.566,
2385
+ "step": 44000
2386
+ },
2387
+ {
2388
+ "epoch": 8.81,
2389
+ "learning_rate": 5.949316966937241e-06,
2390
+ "loss": 1.768,
2391
+ "step": 44500
2392
+ },
2393
+ {
2394
+ "epoch": 8.91,
2395
+ "learning_rate": 5.4543654721837265e-06,
2396
+ "loss": 1.7494,
2397
+ "step": 45000
2398
+ },
2399
+ {
2400
+ "epoch": 8.91,
2401
+ "eval_COMMENT": {
2402
+ "f1": 0.7275605726872247,
2403
+ "number": 6854,
2404
+ "precision": 0.6886890800104248,
2405
+ "recall": 0.7710825795156113
2406
+ },
2407
+ "eval_NAME": {
2408
+ "f1": 0.8160244095378009,
2409
+ "number": 8845,
2410
+ "precision": 0.8156557099288377,
2411
+ "recall": 0.8163934426229508
2412
+ },
2413
+ "eval_QTY": {
2414
+ "f1": 0.9865552072448623,
2415
+ "number": 7152,
2416
+ "precision": 0.9830626128002221,
2417
+ "recall": 0.9900727069351231
2418
+ },
2419
+ "eval_RANGE_END": {
2420
+ "f1": 0.7899159663865547,
2421
+ "number": 105,
2422
+ "precision": 0.706766917293233,
2423
+ "recall": 0.8952380952380953
2424
+ },
2425
+ "eval_UNIT": {
2426
+ "f1": 0.9546817441960078,
2427
+ "number": 5646,
2428
+ "precision": 0.924506387921022,
2429
+ "recall": 0.9868933758413035
2430
+ },
2431
+ "eval_loss": 2.1094605922698975,
2432
+ "eval_overall_accuracy": 0.8318896740369273,
2433
+ "eval_overall_f1": 0.8634685085139848,
2434
+ "eval_overall_precision": 0.8448645031783205,
2435
+ "eval_overall_recall": 0.8829102859939865,
2436
+ "eval_runtime": 10.8603,
2437
+ "eval_samples_per_second": 783.222,
2438
+ "eval_steps_per_second": 24.493,
2439
+ "step": 45000
2440
+ },
2441
+ {
2442
+ "epoch": 9.01,
2443
+ "learning_rate": 4.959413977430212e-06,
2444
+ "loss": 1.7068,
2445
+ "step": 45500
2446
+ },
2447
+ {
2448
+ "epoch": 9.11,
2449
+ "learning_rate": 4.4644624826766974e-06,
2450
+ "loss": 1.6805,
2451
+ "step": 46000
2452
+ },
2453
+ {
2454
+ "epoch": 9.11,
2455
+ "eval_COMMENT": {
2456
+ "f1": 0.727134881797505,
2457
+ "number": 6854,
2458
+ "precision": 0.6890920966688439,
2459
+ "recall": 0.7696235774730085
2460
+ },
2461
+ "eval_NAME": {
2462
+ "f1": 0.8148566905986773,
2463
+ "number": 8845,
2464
+ "precision": 0.8149027589326097,
2465
+ "recall": 0.8148106274731487
2466
+ },
2467
+ "eval_QTY": {
2468
+ "f1": 0.9866963850386571,
2469
+ "number": 7152,
2470
+ "precision": 0.9830673143650243,
2471
+ "recall": 0.9903523489932886
2472
+ },
2473
+ "eval_RANGE_END": {
2474
+ "f1": 0.7950819672131149,
2475
+ "number": 105,
2476
+ "precision": 0.697841726618705,
2477
+ "recall": 0.9238095238095239
2478
+ },
2479
+ "eval_UNIT": {
2480
+ "f1": 0.9543739279588336,
2481
+ "number": 5646,
2482
+ "precision": 0.9251745926172265,
2483
+ "recall": 0.9854764434998229
2484
+ },
2485
+ "eval_loss": 2.113201856613159,
2486
+ "eval_overall_accuracy": 0.8326874857533622,
2487
+ "eval_overall_f1": 0.8630322106091448,
2488
+ "eval_overall_precision": 0.8448939947081087,
2489
+ "eval_overall_recall": 0.8819662960632124,
2490
+ "eval_runtime": 9.5944,
2491
+ "eval_samples_per_second": 886.557,
2492
+ "eval_steps_per_second": 27.724,
2493
+ "step": 46000
2494
+ },
2495
+ {
2496
+ "epoch": 9.21,
2497
+ "learning_rate": 3.969510987923184e-06,
2498
+ "loss": 1.7258,
2499
+ "step": 46500
2500
+ },
2501
+ {
2502
+ "epoch": 9.31,
2503
+ "learning_rate": 3.4745594931696697e-06,
2504
+ "loss": 1.6867,
2505
+ "step": 47000
2506
+ },
2507
+ {
2508
+ "epoch": 9.31,
2509
+ "eval_COMMENT": {
2510
+ "f1": 0.7311783679912154,
2511
+ "number": 6854,
2512
+ "precision": 0.6902941557600104,
2513
+ "recall": 0.7772103880945433
2514
+ },
2515
+ "eval_NAME": {
2516
+ "f1": 0.8176065092100803,
2517
+ "number": 8845,
2518
+ "precision": 0.8172370947701344,
2519
+ "recall": 0.817976257772753
2520
+ },
2521
+ "eval_QTY": {
2522
+ "f1": 0.9865533337978123,
2523
+ "number": 7152,
2524
+ "precision": 0.9831967782252465,
2525
+ "recall": 0.9899328859060402
2526
+ },
2527
+ "eval_RANGE_END": {
2528
+ "f1": 0.7932489451476793,
2529
+ "number": 105,
2530
+ "precision": 0.7121212121212122,
2531
+ "recall": 0.8952380952380953
2532
+ },
2533
+ "eval_UNIT": {
2534
+ "f1": 0.9545610425240054,
2535
+ "number": 5646,
2536
+ "precision": 0.925058158856763,
2537
+ "recall": 0.9860077931278781
2538
+ },
2539
+ "eval_loss": 2.1125941276550293,
2540
+ "eval_overall_accuracy": 0.8326115036851303,
2541
+ "eval_overall_f1": 0.8647198537327205,
2542
+ "eval_overall_precision": 0.8456602386283881,
2543
+ "eval_overall_recall": 0.8846584154954199,
2544
+ "eval_runtime": 11.2863,
2545
+ "eval_samples_per_second": 753.659,
2546
+ "eval_steps_per_second": 23.568,
2547
+ "step": 47000
2548
+ },
2549
+ {
2550
+ "epoch": 9.4,
2551
+ "learning_rate": 2.979607998416155e-06,
2552
+ "loss": 1.6794,
2553
+ "step": 47500
2554
+ },
2555
+ {
2556
+ "epoch": 9.5,
2557
+ "learning_rate": 2.484656503662641e-06,
2558
+ "loss": 1.7212,
2559
+ "step": 48000
2560
+ },
2561
+ {
2562
+ "epoch": 9.5,
2563
+ "eval_COMMENT": {
2564
+ "f1": 0.7277605779153767,
2565
+ "number": 6854,
2566
+ "precision": 0.6885822158573103,
2567
+ "recall": 0.7716661803326524
2568
+ },
2569
+ "eval_NAME": {
2570
+ "f1": 0.8148064424978807,
2571
+ "number": 8845,
2572
+ "precision": 0.8145762711864407,
2573
+ "recall": 0.8150367439231204
2574
+ },
2575
+ "eval_QTY": {
2576
+ "f1": 0.9864120967179988,
2577
+ "number": 7152,
2578
+ "precision": 0.98319211001528,
2579
+ "recall": 0.9896532438478747
2580
+ },
2581
+ "eval_RANGE_END": {
2582
+ "f1": 0.7901234567901234,
2583
+ "number": 105,
2584
+ "precision": 0.6956521739130435,
2585
+ "recall": 0.9142857142857143
2586
+ },
2587
+ "eval_UNIT": {
2588
+ "f1": 0.9545104086353122,
2589
+ "number": 5646,
2590
+ "precision": 0.9243404678944749,
2591
+ "recall": 0.9867162592986185
2592
+ },
2593
+ "eval_loss": 2.105802297592163,
2594
+ "eval_overall_accuracy": 0.8318706785198693,
2595
+ "eval_overall_f1": 0.86305280612681,
2596
+ "eval_overall_precision": 0.8443886937614986,
2597
+ "eval_overall_recall": 0.8825606600936997,
2598
+ "eval_runtime": 10.3961,
2599
+ "eval_samples_per_second": 818.189,
2600
+ "eval_steps_per_second": 25.586,
2601
+ "step": 48000
2602
+ },
2603
+ {
2604
+ "epoch": 9.6,
2605
+ "learning_rate": 1.989705008909127e-06,
2606
+ "loss": 1.6992,
2607
+ "step": 48500
2608
+ },
2609
+ {
2610
+ "epoch": 9.7,
2611
+ "learning_rate": 1.4947535141556129e-06,
2612
+ "loss": 1.6952,
2613
+ "step": 49000
2614
+ },
2615
+ {
2616
+ "epoch": 9.7,
2617
+ "eval_COMMENT": {
2618
+ "f1": 0.7261049723756906,
2619
+ "number": 6854,
2620
+ "precision": 0.6893522161028062,
2621
+ "recall": 0.7669973737963233
2622
+ },
2623
+ "eval_NAME": {
2624
+ "f1": 0.81525854761232,
2625
+ "number": 8845,
2626
+ "precision": 0.8150282485875706,
2627
+ "recall": 0.8154889768230639
2628
+ },
2629
+ "eval_QTY": {
2630
+ "f1": 0.9866276640200585,
2631
+ "number": 7152,
2632
+ "precision": 0.9829308909242298,
2633
+ "recall": 0.9903523489932886
2634
+ },
2635
+ "eval_RANGE_END": {
2636
+ "f1": 0.7916666666666667,
2637
+ "number": 105,
2638
+ "precision": 0.7037037037037037,
2639
+ "recall": 0.9047619047619048
2640
+ },
2641
+ "eval_UNIT": {
2642
+ "f1": 0.9544792113159023,
2643
+ "number": 5646,
2644
+ "precision": 0.9249044691809271,
2645
+ "recall": 0.9860077931278781
2646
+ },
2647
+ "eval_loss": 2.1103529930114746,
2648
+ "eval_overall_accuracy": 0.8311488488716663,
2649
+ "eval_overall_f1": 0.8629658783668163,
2650
+ "eval_overall_precision": 0.8451199892747017,
2651
+ "eval_overall_recall": 0.881581707572897,
2652
+ "eval_runtime": 11.1488,
2653
+ "eval_samples_per_second": 762.95,
2654
+ "eval_steps_per_second": 23.859,
2655
+ "step": 49000
2656
+ },
2657
+ {
2658
+ "epoch": 9.8,
2659
+ "learning_rate": 9.998020194020988e-07,
2660
+ "loss": 1.7282,
2661
+ "step": 49500
2662
+ },
2663
+ {
2664
+ "epoch": 9.9,
2665
+ "learning_rate": 5.048505246485845e-07,
2666
+ "loss": 1.7128,
2667
+ "step": 50000
2668
+ },
2669
+ {
2670
+ "epoch": 9.9,
2671
+ "eval_COMMENT": {
2672
+ "f1": 0.7280375120673009,
2673
+ "number": 6854,
2674
+ "precision": 0.6902458158995816,
2675
+ "recall": 0.7702071782900496
2676
+ },
2677
+ "eval_NAME": {
2678
+ "f1": 0.8154846001695395,
2679
+ "number": 8845,
2680
+ "precision": 0.8152542372881356,
2681
+ "recall": 0.8157150932730356
2682
+ },
2683
+ "eval_QTY": {
2684
+ "f1": 0.9866276640200585,
2685
+ "number": 7152,
2686
+ "precision": 0.9829308909242298,
2687
+ "recall": 0.9903523489932886
2688
+ },
2689
+ "eval_RANGE_END": {
2690
+ "f1": 0.7851239669421487,
2691
+ "number": 105,
2692
+ "precision": 0.6934306569343066,
2693
+ "recall": 0.9047619047619048
2694
+ },
2695
+ "eval_UNIT": {
2696
+ "f1": 0.9546351084812623,
2697
+ "number": 5646,
2698
+ "precision": 0.9253532834580216,
2699
+ "recall": 0.9858306765851931
2700
+ },
2701
+ "eval_loss": 2.104012966156006,
2702
+ "eval_overall_accuracy": 0.8311298533546083,
2703
+ "eval_overall_f1": 0.8634575250607274,
2704
+ "eval_overall_precision": 0.8453242229367631,
2705
+ "eval_overall_recall": 0.8823858471435564,
2706
+ "eval_runtime": 10.6017,
2707
+ "eval_samples_per_second": 802.322,
2708
+ "eval_steps_per_second": 25.09,
2709
+ "step": 50000
2710
+ },
2711
+ {
2712
+ "epoch": 10.0,
2713
+ "learning_rate": 9.899029895070283e-09,
2714
+ "loss": 1.7318,
2715
+ "step": 50500
2716
+ },
2717
+ {
2718
+ "epoch": 10.0,
2719
+ "step": 50510,
2720
+ "total_flos": 1554473524185192.0,
2721
+ "train_loss": 2.2027091482279917,
2722
+ "train_runtime": 3516.1179,
2723
+ "train_samples_per_second": 459.606,
2724
+ "train_steps_per_second": 14.365
2725
  }
2726
  ],
2727
  "logging_steps": 500,
2728
+ "max_steps": 50510,
2729
+ "num_train_epochs": 10,
2730
+ "save_steps": 1000,
2731
+ "total_flos": 1554473524185192.0,
2732
  "trial_name": null,
2733
  "trial_params": null
2734
  }
training_args.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:445f885f648d22fc4ab9f3caa1ac96f712e52c6cede27f3855cfdc76d2db8dfa
3
  size 4155
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f999b5dc64fef85136a202bec190f0c095cc323f240e95e5cf7d43d4c8eceeab
3
  size 4155
validation_results.json CHANGED
@@ -1,41 +1,41 @@
1
  {
2
- "epoch": 3.0,
3
  "eval_COMMENT": {
4
- "f1": 0.6959761549925485,
5
- "number": 6922,
6
- "precision": 0.6552295918367347,
7
- "recall": 0.7421265530193586
8
  },
9
  "eval_NAME": {
10
- "f1": 0.8171377097173741,
11
- "number": 8833,
12
- "precision": 0.8127449882405644,
13
- "recall": 0.8215781727612362
14
  },
15
  "eval_QTY": {
16
- "f1": 0.9830914470903199,
17
- "number": 7092,
18
- "precision": 0.9823993241340467,
19
- "recall": 0.983784545967287
20
  },
21
  "eval_RANGE_END": {
22
- "f1": 0.75,
23
- "number": 88,
24
- "precision": 0.65,
25
- "recall": 0.8863636363636364
26
  },
27
  "eval_UNIT": {
28
- "f1": 0.9497026338147834,
29
- "number": 5707,
30
- "precision": 0.9218208807521029,
31
- "recall": 0.9793236376379885
32
  },
33
- "eval_loss": 2.639784336090088,
34
- "eval_overall_accuracy": 0.8287289687859962,
35
- "eval_overall_f1": 0.8531416110126756,
36
- "eval_overall_precision": 0.8331004192453584,
37
- "eval_overall_recall": 0.8741707981286223,
38
- "eval_runtime": 13.2958,
39
- "eval_samples_per_second": 639.753,
40
- "eval_steps_per_second": 20.006
41
  }
 
1
  {
2
+ "epoch": 10.0,
3
  "eval_COMMENT": {
4
+ "f1": 0.7251437677544517,
5
+ "number": 6854,
6
+ "precision": 0.6904604829133131,
7
+ "recall": 0.7634957688940764
8
  },
9
  "eval_NAME": {
10
+ "f1": 0.8154846001695395,
11
+ "number": 8845,
12
+ "precision": 0.8152542372881356,
13
+ "recall": 0.8157150932730356
14
  },
15
  "eval_QTY": {
16
+ "f1": 0.9866220735785953,
17
+ "number": 7152,
18
+ "precision": 0.9833333333333333,
19
+ "recall": 0.9899328859060402
20
  },
21
  "eval_RANGE_END": {
22
+ "f1": 0.8,
23
+ "number": 105,
24
+ "precision": 0.7,
25
+ "recall": 0.9333333333333333
26
  },
27
  "eval_UNIT": {
28
+ "f1": 0.9544557852302942,
29
+ "number": 5646,
30
+ "precision": 0.9253284550141361,
31
+ "recall": 0.9854764434998229
32
  },
33
+ "eval_loss": 2.1034367084503174,
34
+ "eval_overall_accuracy": 0.830616974394043,
35
+ "eval_overall_f1": 0.8629076459303919,
36
+ "eval_overall_precision": 0.8458129071251091,
37
+ "eval_overall_recall": 0.8807076428221803,
38
+ "eval_runtime": 11.5695,
39
+ "eval_samples_per_second": 735.208,
40
+ "eval_steps_per_second": 22.991
41
  }