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---
tags:
- generated_from_trainer
datasets:
- funsd
model-index:
- name: OCR-LM-v1
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# OCR-LM-v1
This model is a fine-tuned version of [jinhybr/layoutlm-funsd-pytorch](https://huggingface.co/jinhybr/layoutlm-funsd-pytorch) on the funsd dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1740
- Answer: {'precision': 0.7201327433628318, 'recall': 0.8046971569839307, 'f1': 0.7600700525394046, 'number': 809}
- Header: {'precision': 0.4246575342465753, 'recall': 0.5210084033613446, 'f1': 0.46792452830188674, 'number': 119}
- Question: {'precision': 0.8236380424746076, 'recall': 0.8375586854460094, 'f1': 0.8305400372439479, 'number': 1065}
- Overall Precision: 0.7525
- Overall Recall: 0.8053
- Overall F1: 0.7780
- Overall Accuracy: 0.8146
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Answer | Header | Question | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
| 0.3093 | 1.0 | 10 | 0.7358 | {'precision': 0.7053763440860215, 'recall': 0.8108776266996292, 'f1': 0.7544565842438183, 'number': 809} | {'precision': 0.33587786259541985, 'recall': 0.3697478991596639, 'f1': 0.35200000000000004, 'number': 119} | {'precision': 0.7900900900900901, 'recall': 0.8234741784037559, 'f1': 0.8064367816091954, 'number': 1065} | 0.7264 | 0.7913 | 0.7574 | 0.8064 |
| 0.2626 | 2.0 | 20 | 0.7389 | {'precision': 0.7217090069284064, 'recall': 0.7725587144622992, 'f1': 0.746268656716418, 'number': 809} | {'precision': 0.33986928104575165, 'recall': 0.4369747899159664, 'f1': 0.3823529411764706, 'number': 119} | {'precision': 0.7693661971830986, 'recall': 0.8206572769953052, 'f1': 0.79418446160836, 'number': 1065} | 0.7197 | 0.7782 | 0.7478 | 0.7999 |
| 0.2096 | 3.0 | 30 | 0.7834 | {'precision': 0.7417452830188679, 'recall': 0.7775030902348579, 'f1': 0.7592033796016897, 'number': 809} | {'precision': 0.3724137931034483, 'recall': 0.453781512605042, 'f1': 0.40909090909090906, 'number': 119} | {'precision': 0.7889087656529516, 'recall': 0.828169014084507, 'f1': 0.8080622995877232, 'number': 1065} | 0.7414 | 0.7852 | 0.7627 | 0.8003 |
| 0.1755 | 4.0 | 40 | 0.7856 | {'precision': 0.6917372881355932, 'recall': 0.8071693448702101, 'f1': 0.7450085567598402, 'number': 809} | {'precision': 0.35135135135135137, 'recall': 0.4369747899159664, 'f1': 0.3895131086142322, 'number': 119} | {'precision': 0.7893333333333333, 'recall': 0.8338028169014085, 'f1': 0.810958904109589, 'number': 1065} | 0.7185 | 0.7993 | 0.7568 | 0.8005 |
| 0.1421 | 5.0 | 50 | 0.8088 | {'precision': 0.7144444444444444, 'recall': 0.7948084054388134, 'f1': 0.7524868344060853, 'number': 809} | {'precision': 0.39436619718309857, 'recall': 0.47058823529411764, 'f1': 0.4291187739463601, 'number': 119} | {'precision': 0.7915543575920935, 'recall': 0.8272300469483568, 'f1': 0.8089990817263545, 'number': 1065} | 0.7332 | 0.7928 | 0.7618 | 0.8014 |
| 0.1235 | 6.0 | 60 | 0.8637 | {'precision': 0.7262313860252004, 'recall': 0.7836835599505563, 'f1': 0.7538644470868016, 'number': 809} | {'precision': 0.37410071942446044, 'recall': 0.4369747899159664, 'f1': 0.40310077519379844, 'number': 119} | {'precision': 0.7994604316546763, 'recall': 0.8347417840375587, 'f1': 0.8167202572347267, 'number': 1065} | 0.7415 | 0.7903 | 0.7651 | 0.8026 |
| 0.1057 | 7.0 | 70 | 0.8848 | {'precision': 0.7323290845886443, 'recall': 0.7812113720642769, 'f1': 0.7559808612440193, 'number': 809} | {'precision': 0.3986013986013986, 'recall': 0.4789915966386555, 'f1': 0.4351145038167939, 'number': 119} | {'precision': 0.7989080982711556, 'recall': 0.8244131455399061, 'f1': 0.8114602587800368, 'number': 1065} | 0.7444 | 0.7863 | 0.7648 | 0.7959 |
| 0.1054 | 8.0 | 80 | 0.9131 | {'precision': 0.7241758241758242, 'recall': 0.8145859085290482, 'f1': 0.7667248400232693, 'number': 809} | {'precision': 0.41916167664670656, 'recall': 0.5882352941176471, 'f1': 0.4895104895104894, 'number': 119} | {'precision': 0.8152686145146089, 'recall': 0.812206572769953, 'f1': 0.8137347130761995, 'number': 1065} | 0.7456 | 0.7998 | 0.7717 | 0.8021 |
| 0.0814 | 9.0 | 90 | 0.9202 | {'precision': 0.7013129102844639, 'recall': 0.792336217552534, 'f1': 0.7440510737086476, 'number': 809} | {'precision': 0.42758620689655175, 'recall': 0.5210084033613446, 'f1': 0.4696969696969697, 'number': 119} | {'precision': 0.8076572470373746, 'recall': 0.831924882629108, 'f1': 0.8196114708603145, 'number': 1065} | 0.7370 | 0.7973 | 0.7660 | 0.8017 |
| 0.0722 | 10.0 | 100 | 0.9309 | {'precision': 0.711211778029445, 'recall': 0.7762669962917181, 'f1': 0.7423167848699764, 'number': 809} | {'precision': 0.3816793893129771, 'recall': 0.42016806722689076, 'f1': 0.4, 'number': 119} | {'precision': 0.8154706430568499, 'recall': 0.8215962441314554, 'f1': 0.8185219831618334, 'number': 1065} | 0.7441 | 0.7792 | 0.7613 | 0.8029 |
| 0.062 | 11.0 | 110 | 0.9820 | {'precision': 0.717391304347826, 'recall': 0.7750309023485785, 'f1': 0.7450980392156862, 'number': 809} | {'precision': 0.37735849056603776, 'recall': 0.5042016806722689, 'f1': 0.43165467625899284, 'number': 119} | {'precision': 0.7917414721723519, 'recall': 0.828169014084507, 'f1': 0.8095456631482332, 'number': 1065} | 0.7308 | 0.7873 | 0.7580 | 0.7977 |
| 0.056 | 12.0 | 120 | 0.9787 | {'precision': 0.7014270032930845, 'recall': 0.7898640296662547, 'f1': 0.7430232558139536, 'number': 809} | {'precision': 0.3881578947368421, 'recall': 0.4957983193277311, 'f1': 0.4354243542435424, 'number': 119} | {'precision': 0.8092592592592592, 'recall': 0.8206572769953052, 'f1': 0.814918414918415, 'number': 1065} | 0.7336 | 0.7888 | 0.7602 | 0.8069 |
| 0.0521 | 13.0 | 130 | 1.0012 | {'precision': 0.7094972067039106, 'recall': 0.7849196538936959, 'f1': 0.7453051643192488, 'number': 809} | {'precision': 0.39568345323741005, 'recall': 0.46218487394957986, 'f1': 0.4263565891472868, 'number': 119} | {'precision': 0.8278457196613358, 'recall': 0.8262910798122066, 'f1': 0.8270676691729324, 'number': 1065} | 0.7487 | 0.7878 | 0.7677 | 0.8054 |
| 0.0512 | 14.0 | 140 | 1.0412 | {'precision': 0.7181818181818181, 'recall': 0.7812113720642769, 'f1': 0.7483718176435761, 'number': 809} | {'precision': 0.417910447761194, 'recall': 0.47058823529411764, 'f1': 0.4426877470355731, 'number': 119} | {'precision': 0.7925531914893617, 'recall': 0.8394366197183099, 'f1': 0.8153214774281805, 'number': 1065} | 0.7386 | 0.7938 | 0.7652 | 0.7924 |
| 0.0422 | 15.0 | 150 | 1.0369 | {'precision': 0.6987315010570825, 'recall': 0.8170580964153276, 'f1': 0.7532763532763533, 'number': 809} | {'precision': 0.4222222222222222, 'recall': 0.4789915966386555, 'f1': 0.44881889763779526, 'number': 119} | {'precision': 0.8138248847926267, 'recall': 0.8291079812206573, 'f1': 0.8213953488372093, 'number': 1065} | 0.7392 | 0.8033 | 0.7699 | 0.8060 |
| 0.041 | 16.0 | 160 | 1.0669 | {'precision': 0.7108843537414966, 'recall': 0.7750309023485785, 'f1': 0.7415730337078651, 'number': 809} | {'precision': 0.4117647058823529, 'recall': 0.47058823529411764, 'f1': 0.4392156862745098, 'number': 119} | {'precision': 0.7953736654804271, 'recall': 0.8394366197183099, 'f1': 0.8168113293741435, 'number': 1065} | 0.7362 | 0.7913 | 0.7628 | 0.7989 |
| 0.0338 | 17.0 | 170 | 1.0376 | {'precision': 0.7056277056277056, 'recall': 0.8059332509270705, 'f1': 0.7524523946912869, 'number': 809} | {'precision': 0.4117647058823529, 'recall': 0.5294117647058824, 'f1': 0.463235294117647, 'number': 119} | {'precision': 0.8159111933395005, 'recall': 0.828169014084507, 'f1': 0.8219944082013048, 'number': 1065} | 0.7400 | 0.8013 | 0.7695 | 0.8062 |
| 0.0343 | 18.0 | 180 | 1.0498 | {'precision': 0.7165178571428571, 'recall': 0.7935723114956736, 'f1': 0.7530791788856306, 'number': 809} | {'precision': 0.42953020134228187, 'recall': 0.5378151260504201, 'f1': 0.47761194029850745, 'number': 119} | {'precision': 0.8065693430656934, 'recall': 0.8300469483568075, 'f1': 0.8181397501156872, 'number': 1065} | 0.7426 | 0.7978 | 0.7692 | 0.8035 |
| 0.0294 | 19.0 | 190 | 1.0455 | {'precision': 0.7022900763358778, 'recall': 0.796044499381953, 'f1': 0.7462340672074159, 'number': 809} | {'precision': 0.42857142857142855, 'recall': 0.5042016806722689, 'f1': 0.4633204633204633, 'number': 119} | {'precision': 0.8277153558052435, 'recall': 0.8300469483568075, 'f1': 0.8288795124238162, 'number': 1065} | 0.7473 | 0.7968 | 0.7712 | 0.8077 |
| 0.0302 | 20.0 | 200 | 1.0363 | {'precision': 0.7261363636363637, 'recall': 0.7898640296662547, 'f1': 0.7566607460035524, 'number': 809} | {'precision': 0.4225352112676056, 'recall': 0.5042016806722689, 'f1': 0.45977011494252873, 'number': 119} | {'precision': 0.8149498632634458, 'recall': 0.8394366197183099, 'f1': 0.8270120259019426, 'number': 1065} | 0.7518 | 0.7993 | 0.7748 | 0.8073 |
| 0.0232 | 21.0 | 210 | 1.0406 | {'precision': 0.7085152838427947, 'recall': 0.8022249690976514, 'f1': 0.7524637681159421, 'number': 809} | {'precision': 0.4142857142857143, 'recall': 0.48739495798319327, 'f1': 0.4478764478764479, 'number': 119} | {'precision': 0.8198529411764706, 'recall': 0.8375586854460094, 'f1': 0.8286112401300512, 'number': 1065} | 0.7458 | 0.8023 | 0.7730 | 0.8096 |
| 0.025 | 22.0 | 220 | 1.0627 | {'precision': 0.7220338983050848, 'recall': 0.7898640296662547, 'f1': 0.7544273907910272, 'number': 809} | {'precision': 0.4306569343065693, 'recall': 0.4957983193277311, 'f1': 0.46093749999999994, 'number': 119} | {'precision': 0.8222836095764272, 'recall': 0.8384976525821596, 'f1': 0.8303114830311482, 'number': 1065} | 0.7547 | 0.7983 | 0.7759 | 0.8125 |
| 0.0203 | 23.0 | 230 | 1.0621 | {'precision': 0.7149122807017544, 'recall': 0.8059332509270705, 'f1': 0.757699012202208, 'number': 809} | {'precision': 0.42857142857142855, 'recall': 0.5042016806722689, 'f1': 0.4633204633204633, 'number': 119} | {'precision': 0.8182656826568265, 'recall': 0.8328638497652582, 'f1': 0.8255002326663564, 'number': 1065} | 0.7486 | 0.8023 | 0.7745 | 0.8139 |
| 0.0214 | 24.0 | 240 | 1.1079 | {'precision': 0.7268571428571429, 'recall': 0.7861557478368356, 'f1': 0.7553444180522566, 'number': 809} | {'precision': 0.40397350993377484, 'recall': 0.5126050420168067, 'f1': 0.45185185185185184, 'number': 119} | {'precision': 0.8148820326678766, 'recall': 0.8431924882629108, 'f1': 0.8287955699123213, 'number': 1065} | 0.7495 | 0.8003 | 0.7741 | 0.8050 |
| 0.0179 | 25.0 | 250 | 1.0955 | {'precision': 0.7149270482603816, 'recall': 0.7873918417799752, 'f1': 0.7494117647058823, 'number': 809} | {'precision': 0.4057971014492754, 'recall': 0.47058823529411764, 'f1': 0.43579766536964987, 'number': 119} | {'precision': 0.8115942028985508, 'recall': 0.8413145539906103, 'f1': 0.826187183033656, 'number': 1065} | 0.7450 | 0.7973 | 0.7702 | 0.8075 |
| 0.0181 | 26.0 | 260 | 1.0775 | {'precision': 0.7172949002217295, 'recall': 0.799752781211372, 'f1': 0.7562828755113968, 'number': 809} | {'precision': 0.4088050314465409, 'recall': 0.5462184873949579, 'f1': 0.4676258992805755, 'number': 119} | {'precision': 0.8122151321786691, 'recall': 0.8366197183098592, 'f1': 0.8242368177613321, 'number': 1065} | 0.7428 | 0.8043 | 0.7723 | 0.8103 |
| 0.0169 | 27.0 | 270 | 1.0667 | {'precision': 0.7176339285714286, 'recall': 0.7948084054388134, 'f1': 0.7542521994134898, 'number': 809} | {'precision': 0.41721854304635764, 'recall': 0.5294117647058824, 'f1': 0.4666666666666667, 'number': 119} | {'precision': 0.821656050955414, 'recall': 0.847887323943662, 'f1': 0.8345656192236599, 'number': 1065} | 0.7498 | 0.8073 | 0.7775 | 0.8115 |
| 0.0164 | 28.0 | 280 | 1.0798 | {'precision': 0.7106382978723405, 'recall': 0.8257107540173053, 'f1': 0.7638650657518582, 'number': 809} | {'precision': 0.42567567567567566, 'recall': 0.5294117647058824, 'f1': 0.47191011235955055, 'number': 119} | {'precision': 0.8265682656826568, 'recall': 0.8413145539906103, 'f1': 0.8338762214983713, 'number': 1065} | 0.7491 | 0.8164 | 0.7813 | 0.8152 |
| 0.0178 | 29.0 | 290 | 1.0944 | {'precision': 0.7214611872146118, 'recall': 0.7812113720642769, 'f1': 0.7501483679525223, 'number': 809} | {'precision': 0.4496124031007752, 'recall': 0.48739495798319327, 'f1': 0.467741935483871, 'number': 119} | {'precision': 0.8191881918819188, 'recall': 0.8338028169014085, 'f1': 0.8264308980921358, 'number': 1065} | 0.7554 | 0.7918 | 0.7732 | 0.8136 |
| 0.0151 | 30.0 | 300 | 1.0994 | {'precision': 0.7141292442497261, 'recall': 0.8059332509270705, 'f1': 0.7572590011614402, 'number': 809} | {'precision': 0.43795620437956206, 'recall': 0.5042016806722689, 'f1': 0.46875, 'number': 119} | {'precision': 0.8211981566820277, 'recall': 0.8366197183098592, 'f1': 0.8288372093023256, 'number': 1065} | 0.7508 | 0.8043 | 0.7766 | 0.8151 |
| 0.0127 | 31.0 | 310 | 1.1177 | {'precision': 0.7144420131291028, 'recall': 0.8071693448702101, 'f1': 0.7579802669762042, 'number': 809} | {'precision': 0.4264705882352941, 'recall': 0.48739495798319327, 'f1': 0.4549019607843137, 'number': 119} | {'precision': 0.82483781278962, 'recall': 0.8356807511737089, 'f1': 0.8302238805970149, 'number': 1065} | 0.7520 | 0.8033 | 0.7768 | 0.8136 |
| 0.0123 | 32.0 | 320 | 1.1295 | {'precision': 0.7280799112097669, 'recall': 0.8108776266996292, 'f1': 0.7672514619883041, 'number': 809} | {'precision': 0.4316546762589928, 'recall': 0.5042016806722689, 'f1': 0.46511627906976744, 'number': 119} | {'precision': 0.8176043557168784, 'recall': 0.8460093896713615, 'f1': 0.8315643747115828, 'number': 1065} | 0.7549 | 0.8113 | 0.7821 | 0.8127 |
| 0.0105 | 33.0 | 330 | 1.1422 | {'precision': 0.717439293598234, 'recall': 0.8034610630407911, 'f1': 0.7580174927113702, 'number': 809} | {'precision': 0.427536231884058, 'recall': 0.4957983193277311, 'f1': 0.4591439688715953, 'number': 119} | {'precision': 0.8168498168498168, 'recall': 0.8375586854460094, 'f1': 0.8270746407046824, 'number': 1065} | 0.7495 | 0.8033 | 0.7755 | 0.8110 |
| 0.0099 | 34.0 | 340 | 1.1476 | {'precision': 0.7194323144104804, 'recall': 0.8145859085290482, 'f1': 0.7640579710144928, 'number': 809} | {'precision': 0.43478260869565216, 'recall': 0.5042016806722689, 'f1': 0.4669260700389105, 'number': 119} | {'precision': 0.8256880733944955, 'recall': 0.8450704225352113, 'f1': 0.8352668213457076, 'number': 1065} | 0.7551 | 0.8123 | 0.7827 | 0.8132 |
| 0.0115 | 35.0 | 350 | 1.1590 | {'precision': 0.7200878155872668, 'recall': 0.8108776266996292, 'f1': 0.7627906976744185, 'number': 809} | {'precision': 0.4125874125874126, 'recall': 0.4957983193277311, 'f1': 0.450381679389313, 'number': 119} | {'precision': 0.8325581395348837, 'recall': 0.8403755868544601, 'f1': 0.8364485981308412, 'number': 1065} | 0.7562 | 0.8078 | 0.7812 | 0.8129 |
| 0.0098 | 36.0 | 360 | 1.1619 | {'precision': 0.7271714922048997, 'recall': 0.8071693448702101, 'f1': 0.7650849443468072, 'number': 809} | {'precision': 0.41379310344827586, 'recall': 0.5042016806722689, 'f1': 0.45454545454545453, 'number': 119} | {'precision': 0.8226691042047533, 'recall': 0.8450704225352113, 'f1': 0.8337193144974525, 'number': 1065} | 0.7548 | 0.8093 | 0.7811 | 0.8140 |
| 0.0089 | 37.0 | 370 | 1.1555 | {'precision': 0.7289823008849557, 'recall': 0.8145859085290482, 'f1': 0.7694103911266784, 'number': 809} | {'precision': 0.42857142857142855, 'recall': 0.5042016806722689, 'f1': 0.4633204633204633, 'number': 119} | {'precision': 0.8178571428571428, 'recall': 0.860093896713615, 'f1': 0.8384439359267735, 'number': 1065} | 0.7555 | 0.8204 | 0.7866 | 0.8158 |
| 0.0116 | 38.0 | 380 | 1.1472 | {'precision': 0.7161862527716186, 'recall': 0.7985166872682324, 'f1': 0.7551139684395091, 'number': 809} | {'precision': 0.42962962962962964, 'recall': 0.48739495798319327, 'f1': 0.45669291338582674, 'number': 119} | {'precision': 0.8250460405156538, 'recall': 0.8413145539906103, 'f1': 0.8331008833100882, 'number': 1065} | 0.7537 | 0.8028 | 0.7775 | 0.8152 |
| 0.0089 | 39.0 | 390 | 1.1558 | {'precision': 0.7158590308370044, 'recall': 0.8034610630407911, 'f1': 0.7571345369831101, 'number': 809} | {'precision': 0.41721854304635764, 'recall': 0.5294117647058824, 'f1': 0.4666666666666667, 'number': 119} | {'precision': 0.8302583025830258, 'recall': 0.8450704225352113, 'f1': 0.8375988832014891, 'number': 1065} | 0.7527 | 0.8093 | 0.7800 | 0.8120 |
| 0.0085 | 40.0 | 400 | 1.1576 | {'precision': 0.7169398907103826, 'recall': 0.8108776266996292, 'f1': 0.7610208816705337, 'number': 809} | {'precision': 0.41843971631205673, 'recall': 0.4957983193277311, 'f1': 0.4538461538461538, 'number': 119} | {'precision': 0.8249772105742935, 'recall': 0.8497652582159625, 'f1': 0.8371877890841812, 'number': 1065} | 0.7524 | 0.8128 | 0.7815 | 0.8127 |
| 0.0079 | 41.0 | 410 | 1.1551 | {'precision': 0.716500553709856, 'recall': 0.799752781211372, 'f1': 0.7558411214953271, 'number': 809} | {'precision': 0.44696969696969696, 'recall': 0.4957983193277311, 'f1': 0.47011952191235057, 'number': 119} | {'precision': 0.8264462809917356, 'recall': 0.8450704225352113, 'f1': 0.8356545961002786, 'number': 1065} | 0.7561 | 0.8058 | 0.7802 | 0.8145 |
| 0.0069 | 42.0 | 420 | 1.1656 | {'precision': 0.7169603524229075, 'recall': 0.8046971569839307, 'f1': 0.7582993593476993, 'number': 809} | {'precision': 0.4315068493150685, 'recall': 0.5294117647058824, 'f1': 0.4754716981132075, 'number': 119} | {'precision': 0.8236914600550964, 'recall': 0.8422535211267606, 'f1': 0.8328690807799443, 'number': 1065} | 0.7517 | 0.8083 | 0.7790 | 0.8137 |
| 0.0067 | 43.0 | 430 | 1.1720 | {'precision': 0.7145993413830956, 'recall': 0.8046971569839307, 'f1': 0.7569767441860464, 'number': 809} | {'precision': 0.43661971830985913, 'recall': 0.5210084033613446, 'f1': 0.47509578544061304, 'number': 119} | {'precision': 0.8190909090909091, 'recall': 0.8460093896713615, 'f1': 0.8323325635103926, 'number': 1065} | 0.7497 | 0.8098 | 0.7786 | 0.8126 |
| 0.0083 | 44.0 | 440 | 1.1720 | {'precision': 0.7203579418344519, 'recall': 0.796044499381953, 'f1': 0.756312389900176, 'number': 809} | {'precision': 0.4397163120567376, 'recall': 0.5210084033613446, 'f1': 0.47692307692307695, 'number': 119} | {'precision': 0.8225659690627843, 'recall': 0.8488262910798122, 'f1': 0.8354898336414048, 'number': 1065} | 0.7545 | 0.8078 | 0.7802 | 0.8150 |
| 0.0072 | 45.0 | 450 | 1.1733 | {'precision': 0.727683615819209, 'recall': 0.796044499381953, 'f1': 0.7603305785123966, 'number': 809} | {'precision': 0.4338235294117647, 'recall': 0.4957983193277311, 'f1': 0.4627450980392157, 'number': 119} | {'precision': 0.8209090909090909, 'recall': 0.847887323943662, 'f1': 0.8341801385681292, 'number': 1065} | 0.7572 | 0.8058 | 0.7807 | 0.8148 |
| 0.0092 | 46.0 | 460 | 1.1712 | {'precision': 0.7188888888888889, 'recall': 0.799752781211372, 'f1': 0.7571679344645992, 'number': 809} | {'precision': 0.4306569343065693, 'recall': 0.4957983193277311, 'f1': 0.46093749999999994, 'number': 119} | {'precision': 0.8214285714285714, 'recall': 0.8422535211267606, 'f1': 0.8317107093184979, 'number': 1065} | 0.7529 | 0.8043 | 0.7778 | 0.8146 |
| 0.0063 | 47.0 | 470 | 1.1723 | {'precision': 0.7158590308370044, 'recall': 0.8034610630407911, 'f1': 0.7571345369831101, 'number': 809} | {'precision': 0.4326241134751773, 'recall': 0.5126050420168067, 'f1': 0.4692307692307692, 'number': 119} | {'precision': 0.8212648945921174, 'recall': 0.8413145539906103, 'f1': 0.8311688311688312, 'number': 1065} | 0.7509 | 0.8063 | 0.7776 | 0.8154 |
| 0.0064 | 48.0 | 480 | 1.1740 | {'precision': 0.7166482910694597, 'recall': 0.8034610630407911, 'f1': 0.7575757575757576, 'number': 809} | {'precision': 0.42657342657342656, 'recall': 0.5126050420168067, 'f1': 0.46564885496183206, 'number': 119} | {'precision': 0.8226102941176471, 'recall': 0.8403755868544601, 'f1': 0.8313980492336275, 'number': 1065} | 0.7512 | 0.8058 | 0.7775 | 0.8147 |
| 0.0069 | 49.0 | 490 | 1.1742 | {'precision': 0.7209302325581395, 'recall': 0.8046971569839307, 'f1': 0.7605140186915887, 'number': 809} | {'precision': 0.4246575342465753, 'recall': 0.5210084033613446, 'f1': 0.46792452830188674, 'number': 119} | {'precision': 0.8236380424746076, 'recall': 0.8375586854460094, 'f1': 0.8305400372439479, 'number': 1065} | 0.7528 | 0.8053 | 0.7782 | 0.8145 |
| 0.0062 | 50.0 | 500 | 1.1740 | {'precision': 0.7201327433628318, 'recall': 0.8046971569839307, 'f1': 0.7600700525394046, 'number': 809} | {'precision': 0.4246575342465753, 'recall': 0.5210084033613446, 'f1': 0.46792452830188674, 'number': 119} | {'precision': 0.8236380424746076, 'recall': 0.8375586854460094, 'f1': 0.8305400372439479, 'number': 1065} | 0.7525 | 0.8053 | 0.7780 | 0.8146 |
### Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.1
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