End of training

README.md

@@ -0,0 +1,117 @@
+---
+library_name: transformers
+license: mit
+base_model: microsoft/layoutlm-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- funsd
+model-index:
+- name: layoutlm-funsd
+  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. -->
+
+# layoutlm-funsd
+
+This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-base-uncased) on the funsd dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.1469
+- Answer: {'precision': 0.7396788990825688, 'recall': 0.7972805933250927, 'f1': 0.7674003569303985, 'number': 809}
+- Header: {'precision': 0.45323741007194246, 'recall': 0.5294117647058824, 'f1': 0.48837209302325585, 'number': 119}
+- Question: {'precision': 0.8115279048490394, 'recall': 0.8328638497652582, 'f1': 0.8220574606116775, 'number': 1065}
+- Overall Precision: 0.7581
+- Overall Recall: 0.8003
+- Overall F1: 0.7786
+- Overall Accuracy: 0.8101
+
+## 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: 32
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 50
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Answer                                                                                                   | Header                                                                                                      | Question                                                                                                  | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
+| 0.5224        | 1.0   | 5    | 0.7102          | {'precision': 0.6642636457260556, 'recall': 0.7972805933250927, 'f1': 0.7247191011235956, 'number': 809} | {'precision': 0.22988505747126436, 'recall': 0.16806722689075632, 'f1': 0.19417475728155342, 'number': 119} | {'precision': 0.7172470978441128, 'recall': 0.812206572769953, 'f1': 0.7617789520035227, 'number': 1065}  | 0.6758            | 0.7677         | 0.7188     | 0.7819           |
+| 0.4555        | 2.0   | 10   | 0.7199          | {'precision': 0.7081930415263749, 'recall': 0.7799752781211372, 'f1': 0.7423529411764707, 'number': 809} | {'precision': 0.2302158273381295, 'recall': 0.2689075630252101, 'f1': 0.248062015503876, 'number': 119}     | {'precision': 0.7556719022687609, 'recall': 0.8131455399061033, 'f1': 0.7833559475350521, 'number': 1065} | 0.7027            | 0.7672         | 0.7335     | 0.7984           |
+| 0.3981        | 3.0   | 15   | 0.7216          | {'precision': 0.7238204833141542, 'recall': 0.7775030902348579, 'f1': 0.7497020262216926, 'number': 809} | {'precision': 0.27586206896551724, 'recall': 0.2689075630252101, 'f1': 0.27234042553191484, 'number': 119}  | {'precision': 0.7587681779298546, 'recall': 0.8328638497652582, 'f1': 0.7940913160250672, 'number': 1065} | 0.7187            | 0.7767         | 0.7466     | 0.7924           |
+| 0.351         | 4.0   | 20   | 0.7183          | {'precision': 0.7116022099447514, 'recall': 0.796044499381953, 'f1': 0.751458576429405, 'number': 809}   | {'precision': 0.2890625, 'recall': 0.31092436974789917, 'f1': 0.29959514170040485, 'number': 119}           | {'precision': 0.7548770144189991, 'recall': 0.8356807511737089, 'f1': 0.7932263814616756, 'number': 1065} | 0.7102            | 0.7883         | 0.7472     | 0.8015           |
+| 0.3156        | 5.0   | 25   | 0.7208          | {'precision': 0.7142857142857143, 'recall': 0.7911001236093943, 'f1': 0.750733137829912, 'number': 809}  | {'precision': 0.29931972789115646, 'recall': 0.3697478991596639, 'f1': 0.33082706766917297, 'number': 119}  | {'precision': 0.7864864864864864, 'recall': 0.819718309859155, 'f1': 0.8027586206896551, 'number': 1065}  | 0.7232            | 0.7812         | 0.7511     | 0.8021           |
+| 0.2762        | 6.0   | 30   | 0.7310          | {'precision': 0.7130434782608696, 'recall': 0.8108776266996292, 'f1': 0.7588201272411799, 'number': 809} | {'precision': 0.3178294573643411, 'recall': 0.3445378151260504, 'f1': 0.33064516129032256, 'number': 119}   | {'precision': 0.7694300518134715, 'recall': 0.8366197183098592, 'f1': 0.8016194331983806, 'number': 1065} | 0.7195            | 0.7968         | 0.7562     | 0.8042           |
+| 0.2511        | 7.0   | 35   | 0.7689          | {'precision': 0.7245370370370371, 'recall': 0.7737948084054388, 'f1': 0.7483562462641961, 'number': 809} | {'precision': 0.33116883116883117, 'recall': 0.42857142857142855, 'f1': 0.37362637362637363, 'number': 119} | {'precision': 0.7825311942959001, 'recall': 0.8244131455399061, 'f1': 0.8029263831732967, 'number': 1065} | 0.7266            | 0.7802         | 0.7525     | 0.8036           |
+| 0.227         | 8.0   | 40   | 0.7812          | {'precision': 0.7216721672167217, 'recall': 0.8108776266996292, 'f1': 0.7636786961583235, 'number': 809} | {'precision': 0.34459459459459457, 'recall': 0.42857142857142855, 'f1': 0.38202247191011235, 'number': 119} | {'precision': 0.7940913160250671, 'recall': 0.8328638497652582, 'f1': 0.8130155820348305, 'number': 1065} | 0.7332            | 0.7998         | 0.7651     | 0.8069           |
+| 0.1976        | 9.0   | 45   | 0.7855          | {'precision': 0.7257142857142858, 'recall': 0.7849196538936959, 'f1': 0.7541567695961995, 'number': 809} | {'precision': 0.3691275167785235, 'recall': 0.46218487394957986, 'f1': 0.41044776119402987, 'number': 119}  | {'precision': 0.7937219730941704, 'recall': 0.8309859154929577, 'f1': 0.8119266055045871, 'number': 1065} | 0.7363            | 0.7903         | 0.7623     | 0.8118           |
+| 0.1824        | 10.0  | 50   | 0.7943          | {'precision': 0.7175824175824176, 'recall': 0.8071693448702101, 'f1': 0.7597440372309483, 'number': 809} | {'precision': 0.34868421052631576, 'recall': 0.44537815126050423, 'f1': 0.3911439114391144, 'number': 119}  | {'precision': 0.7878245299910475, 'recall': 0.8262910798122066, 'f1': 0.8065994500458296, 'number': 1065} | 0.7279            | 0.7958         | 0.7603     | 0.8116           |
+| 0.165         | 11.0  | 55   | 0.8219          | {'precision': 0.7301587301587301, 'recall': 0.796044499381953, 'f1': 0.7616794795978711, 'number': 809}  | {'precision': 0.3793103448275862, 'recall': 0.46218487394957986, 'f1': 0.41666666666666663, 'number': 119}  | {'precision': 0.789908256880734, 'recall': 0.8084507042253521, 'f1': 0.7990719257540604, 'number': 1065}  | 0.7369            | 0.7827         | 0.7591     | 0.8095           |
+| 0.148         | 12.0  | 60   | 0.8420          | {'precision': 0.7286821705426356, 'recall': 0.8133498145859085, 'f1': 0.7686915887850466, 'number': 809} | {'precision': 0.4263565891472868, 'recall': 0.46218487394957986, 'f1': 0.4435483870967742, 'number': 119}   | {'precision': 0.7931034482758621, 'recall': 0.8422535211267606, 'f1': 0.8169398907103825, 'number': 1065} | 0.7443            | 0.8078         | 0.7748     | 0.8068           |
+| 0.1358        | 13.0  | 65   | 0.8636          | {'precision': 0.7441037735849056, 'recall': 0.7799752781211372, 'f1': 0.7616173808086903, 'number': 809} | {'precision': 0.3475609756097561, 'recall': 0.4789915966386555, 'f1': 0.40282685512367494, 'number': 119}   | {'precision': 0.7939560439560439, 'recall': 0.8140845070422535, 'f1': 0.8038942976356049, 'number': 1065} | 0.7391            | 0.7802         | 0.7591     | 0.8052           |
+| 0.1179        | 14.0  | 70   | 0.8502          | {'precision': 0.7305122494432071, 'recall': 0.8108776266996292, 'f1': 0.7685998828353838, 'number': 809} | {'precision': 0.41044776119402987, 'recall': 0.46218487394957986, 'f1': 0.43478260869565216, 'number': 119} | {'precision': 0.8116469517743403, 'recall': 0.8375586854460094, 'f1': 0.8243992606284658, 'number': 1065} | 0.7522            | 0.8043         | 0.7774     | 0.8109           |
+| 0.1103        | 15.0  | 75   | 0.8866          | {'precision': 0.7446555819477435, 'recall': 0.7750309023485785, 'f1': 0.7595396729254997, 'number': 809} | {'precision': 0.38461538461538464, 'recall': 0.5042016806722689, 'f1': 0.4363636363636364, 'number': 119}   | {'precision': 0.7989130434782609, 'recall': 0.828169014084507, 'f1': 0.8132780082987551, 'number': 1065}  | 0.7464            | 0.7873         | 0.7663     | 0.8050           |
+| 0.1011        | 16.0  | 80   | 0.9099          | {'precision': 0.7299670691547749, 'recall': 0.8220024721878862, 'f1': 0.7732558139534884, 'number': 809} | {'precision': 0.427536231884058, 'recall': 0.4957983193277311, 'f1': 0.4591439688715953, 'number': 119}     | {'precision': 0.8219944082013048, 'recall': 0.828169014084507, 'f1': 0.8250701590271282, 'number': 1065}  | 0.7568            | 0.8058         | 0.7806     | 0.8090           |
+| 0.0958        | 17.0  | 85   | 0.9277          | {'precision': 0.7565320665083135, 'recall': 0.7873918417799752, 'f1': 0.7716535433070866, 'number': 809} | {'precision': 0.41216216216216217, 'recall': 0.5126050420168067, 'f1': 0.4569288389513108, 'number': 119}   | {'precision': 0.7994604316546763, 'recall': 0.8347417840375587, 'f1': 0.8167202572347267, 'number': 1065} | 0.7550            | 0.7963         | 0.7751     | 0.8064           |
+| 0.0854        | 18.0  | 90   | 0.9437          | {'precision': 0.7286202964652223, 'recall': 0.7898640296662547, 'f1': 0.7580071174377224, 'number': 809} | {'precision': 0.427536231884058, 'recall': 0.4957983193277311, 'f1': 0.4591439688715953, 'number': 119}     | {'precision': 0.8096980786825252, 'recall': 0.8309859154929577, 'f1': 0.8202038924930491, 'number': 1065} | 0.7509            | 0.7943         | 0.7720     | 0.8091           |
+| 0.0776        | 19.0  | 95   | 0.9501          | {'precision': 0.7412587412587412, 'recall': 0.7861557478368356, 'f1': 0.7630473905218957, 'number': 809} | {'precision': 0.42207792207792205, 'recall': 0.5462184873949579, 'f1': 0.47619047619047616, 'number': 119}  | {'precision': 0.8167441860465117, 'recall': 0.8244131455399061, 'f1': 0.8205607476635515, 'number': 1065} | 0.7566            | 0.7923         | 0.7740     | 0.8106           |
+| 0.0691        | 20.0  | 100  | 0.9436          | {'precision': 0.7252502780867631, 'recall': 0.8059332509270705, 'f1': 0.7634660421545667, 'number': 809} | {'precision': 0.4225352112676056, 'recall': 0.5042016806722689, 'f1': 0.45977011494252873, 'number': 119}   | {'precision': 0.812327506899724, 'recall': 0.8291079812206573, 'f1': 0.8206319702602229, 'number': 1065}  | 0.7495            | 0.8003         | 0.7741     | 0.8155           |
+| 0.0661        | 21.0  | 105  | 0.9569          | {'precision': 0.7306397306397306, 'recall': 0.8046971569839307, 'f1': 0.7658823529411766, 'number': 809} | {'precision': 0.4482758620689655, 'recall': 0.5462184873949579, 'f1': 0.49242424242424243, 'number': 119}   | {'precision': 0.8191881918819188, 'recall': 0.8338028169014085, 'f1': 0.8264308980921358, 'number': 1065} | 0.7566            | 0.8048         | 0.7800     | 0.8154           |
+| 0.0607        | 22.0  | 110  | 0.9847          | {'precision': 0.7453703703703703, 'recall': 0.796044499381953, 'f1': 0.7698744769874476, 'number': 809}  | {'precision': 0.4, 'recall': 0.5210084033613446, 'f1': 0.4525547445255475, 'number': 119}                   | {'precision': 0.8136067101584343, 'recall': 0.819718309859155, 'f1': 0.8166510757717493, 'number': 1065}  | 0.7548            | 0.7923         | 0.7731     | 0.8064           |
+| 0.0555        | 23.0  | 115  | 1.0145          | {'precision': 0.7329545454545454, 'recall': 0.7972805933250927, 'f1': 0.7637655417406749, 'number': 809} | {'precision': 0.41007194244604317, 'recall': 0.4789915966386555, 'f1': 0.4418604651162791, 'number': 119}   | {'precision': 0.8061874431301183, 'recall': 0.831924882629108, 'f1': 0.8188539741219962, 'number': 1065}  | 0.7498            | 0.7968         | 0.7726     | 0.8103           |
+| 0.0529        | 24.0  | 120  | 1.0352          | {'precision': 0.7352601156069364, 'recall': 0.7861557478368356, 'f1': 0.7598566308243728, 'number': 809} | {'precision': 0.4013605442176871, 'recall': 0.4957983193277311, 'f1': 0.443609022556391, 'number': 119}     | {'precision': 0.8099630996309963, 'recall': 0.8244131455399061, 'f1': 0.8171242438343416, 'number': 1065} | 0.7505            | 0.7893         | 0.7694     | 0.8062           |
+| 0.0476        | 25.0  | 125  | 1.0199          | {'precision': 0.7428896473265074, 'recall': 0.8071693448702101, 'f1': 0.7736966824644549, 'number': 809} | {'precision': 0.4166666666666667, 'recall': 0.46218487394957986, 'f1': 0.4382470119521913, 'number': 119}   | {'precision': 0.8068902991840435, 'recall': 0.8356807511737089, 'f1': 0.8210332103321034, 'number': 1065} | 0.7559            | 0.8018         | 0.7782     | 0.8138           |
+| 0.0458        | 26.0  | 130  | 1.0451          | {'precision': 0.735632183908046, 'recall': 0.7911001236093943, 'f1': 0.7623585467540203, 'number': 809}  | {'precision': 0.42857142857142855, 'recall': 0.5546218487394958, 'f1': 0.48351648351648346, 'number': 119}  | {'precision': 0.8176691729323309, 'recall': 0.8169014084507042, 'f1': 0.8172851103804604, 'number': 1065} | 0.7548            | 0.7908         | 0.7724     | 0.8089           |
+| 0.0465        | 27.0  | 135  | 1.0510          | {'precision': 0.7526132404181185, 'recall': 0.8009888751545118, 'f1': 0.7760479041916167, 'number': 809} | {'precision': 0.4326241134751773, 'recall': 0.5126050420168067, 'f1': 0.4692307692307692, 'number': 119}    | {'precision': 0.8059836808703535, 'recall': 0.8347417840375587, 'f1': 0.820110701107011, 'number': 1065}  | 0.7591            | 0.8018         | 0.7799     | 0.8069           |
+| 0.0417        | 28.0  | 140  | 1.0477          | {'precision': 0.7445589919816724, 'recall': 0.8034610630407911, 'f1': 0.7728894173602853, 'number': 809} | {'precision': 0.42657342657342656, 'recall': 0.5126050420168067, 'f1': 0.46564885496183206, 'number': 119}  | {'precision': 0.8207985143918292, 'recall': 0.8300469483568075, 'f1': 0.8253968253968254, 'number': 1065} | 0.7621            | 0.8003         | 0.7807     | 0.8090           |
+| 0.0385        | 29.0  | 145  | 1.0789          | {'precision': 0.7428243398392652, 'recall': 0.799752781211372, 'f1': 0.7702380952380953, 'number': 809}  | {'precision': 0.42567567567567566, 'recall': 0.5294117647058824, 'f1': 0.47191011235955055, 'number': 119}  | {'precision': 0.8073059360730593, 'recall': 0.8300469483568075, 'f1': 0.8185185185185184, 'number': 1065} | 0.7540            | 0.7998         | 0.7762     | 0.8054           |
+| 0.0362        | 30.0  | 150  | 1.0647          | {'precision': 0.7347876004592423, 'recall': 0.7911001236093943, 'f1': 0.761904761904762, 'number': 809}  | {'precision': 0.43795620437956206, 'recall': 0.5042016806722689, 'f1': 0.46875, 'number': 119}              | {'precision': 0.8098271155595996, 'recall': 0.8356807511737089, 'f1': 0.822550831792976, 'number': 1065}  | 0.7546            | 0.7978         | 0.7756     | 0.8080           |
+| 0.0336        | 31.0  | 155  | 1.0769          | {'precision': 0.7395715896279594, 'recall': 0.8108776266996292, 'f1': 0.7735849056603773, 'number': 809} | {'precision': 0.46258503401360546, 'recall': 0.5714285714285714, 'f1': 0.5112781954887218, 'number': 119}   | {'precision': 0.8120437956204379, 'recall': 0.8356807511737089, 'f1': 0.8236927348449792, 'number': 1065} | 0.7577            | 0.8098         | 0.7829     | 0.8092           |
+| 0.0305        | 32.0  | 160  | 1.1055          | {'precision': 0.7505800464037123, 'recall': 0.799752781211372, 'f1': 0.7743865948533811, 'number': 809}  | {'precision': 0.4513888888888889, 'recall': 0.5462184873949579, 'f1': 0.494296577946768, 'number': 119}     | {'precision': 0.8072727272727273, 'recall': 0.8338028169014085, 'f1': 0.8203233256351038, 'number': 1065} | 0.7597            | 0.8028         | 0.7807     | 0.8055           |
+| 0.0316        | 33.0  | 165  | 1.0967          | {'precision': 0.7470449172576832, 'recall': 0.7812113720642769, 'f1': 0.7637462235649547, 'number': 809} | {'precision': 0.42857142857142855, 'recall': 0.5546218487394958, 'f1': 0.48351648351648346, 'number': 119}  | {'precision': 0.8098330241187384, 'recall': 0.819718309859155, 'f1': 0.8147456836210919, 'number': 1065}  | 0.7560            | 0.7883         | 0.7718     | 0.8028           |
+| 0.0304        | 34.0  | 170  | 1.1063          | {'precision': 0.7412823397075365, 'recall': 0.8145859085290482, 'f1': 0.7762073027090693, 'number': 809} | {'precision': 0.4397163120567376, 'recall': 0.5210084033613446, 'f1': 0.47692307692307695, 'number': 119}   | {'precision': 0.805956678700361, 'recall': 0.8384976525821596, 'f1': 0.8219052001840772, 'number': 1065}  | 0.7549            | 0.8098         | 0.7814     | 0.8080           |
+| 0.0293        | 35.0  | 175  | 1.1122          | {'precision': 0.7351290684624018, 'recall': 0.8096415327564895, 'f1': 0.7705882352941176, 'number': 809} | {'precision': 0.44370860927152317, 'recall': 0.5630252100840336, 'f1': 0.49629629629629624, 'number': 119}  | {'precision': 0.8063063063063063, 'recall': 0.8403755868544601, 'f1': 0.8229885057471265, 'number': 1065} | 0.7514            | 0.8113         | 0.7802     | 0.8076           |
+| 0.0262        | 36.0  | 180  | 1.0936          | {'precision': 0.7395348837209302, 'recall': 0.7861557478368356, 'f1': 0.762133013780707, 'number': 809}  | {'precision': 0.45454545454545453, 'recall': 0.5462184873949579, 'f1': 0.4961832061068702, 'number': 119}   | {'precision': 0.8188539741219963, 'recall': 0.831924882629108, 'f1': 0.8253376804843968, 'number': 1065}  | 0.7612            | 0.7963         | 0.7783     | 0.8125           |
+| 0.0261        | 37.0  | 185  | 1.1048          | {'precision': 0.740909090909091, 'recall': 0.8059332509270705, 'f1': 0.7720544701006513, 'number': 809}  | {'precision': 0.4621212121212121, 'recall': 0.5126050420168067, 'f1': 0.4860557768924302, 'number': 119}    | {'precision': 0.8023360287511231, 'recall': 0.8384976525821596, 'f1': 0.8200183654729108, 'number': 1065} | 0.7558            | 0.8058         | 0.7800     | 0.8097           |
+| 0.0268        | 38.0  | 190  | 1.1161          | {'precision': 0.7428243398392652, 'recall': 0.799752781211372, 'f1': 0.7702380952380953, 'number': 809}  | {'precision': 0.4482758620689655, 'recall': 0.5462184873949579, 'f1': 0.49242424242424243, 'number': 119}   | {'precision': 0.8114075436982521, 'recall': 0.828169014084507, 'f1': 0.8197026022304833, 'number': 1065}  | 0.7580            | 0.7998         | 0.7783     | 0.8092           |
+| 0.0237        | 39.0  | 195  | 1.1251          | {'precision': 0.7439724454649828, 'recall': 0.8009888751545118, 'f1': 0.7714285714285715, 'number': 809} | {'precision': 0.47368421052631576, 'recall': 0.5294117647058824, 'f1': 0.5, 'number': 119}                  | {'precision': 0.8094804010938924, 'recall': 0.8338028169014085, 'f1': 0.8214616096207216, 'number': 1065} | 0.7611            | 0.8023         | 0.7811     | 0.8088           |
+| 0.022         | 40.0  | 200  | 1.1322          | {'precision': 0.7372593431483578, 'recall': 0.8046971569839307, 'f1': 0.7695035460992907, 'number': 809} | {'precision': 0.4444444444444444, 'recall': 0.5378151260504201, 'f1': 0.4866920152091255, 'number': 119}    | {'precision': 0.8041704442429737, 'recall': 0.8328638497652582, 'f1': 0.8182656826568265, 'number': 1065} | 0.7521            | 0.8038         | 0.7771     | 0.8070           |
+| 0.0229        | 41.0  | 205  | 1.1349          | {'precision': 0.7433831990794016, 'recall': 0.7985166872682324, 'f1': 0.7699642431466032, 'number': 809} | {'precision': 0.44966442953020136, 'recall': 0.5630252100840336, 'f1': 0.5000000000000001, 'number': 119}   | {'precision': 0.8139963167587477, 'recall': 0.8300469483568075, 'f1': 0.8219432821943281, 'number': 1065} | 0.7590            | 0.8013         | 0.7796     | 0.8076           |
+| 0.0208        | 42.0  | 210  | 1.1341          | {'precision': 0.7436194895591647, 'recall': 0.792336217552534, 'f1': 0.7672052663076003, 'number': 809}  | {'precision': 0.4370860927152318, 'recall': 0.5546218487394958, 'f1': 0.48888888888888893, 'number': 119}   | {'precision': 0.8170844939647168, 'recall': 0.8262910798122066, 'f1': 0.8216619981325864, 'number': 1065} | 0.7593            | 0.7963         | 0.7774     | 0.8091           |
+| 0.0202        | 43.0  | 215  | 1.1439          | {'precision': 0.7344632768361582, 'recall': 0.8034610630407911, 'f1': 0.7674144037780402, 'number': 809} | {'precision': 0.45255474452554745, 'recall': 0.5210084033613446, 'f1': 0.484375, 'number': 119}             | {'precision': 0.8127853881278538, 'recall': 0.8356807511737089, 'f1': 0.824074074074074, 'number': 1065}  | 0.7567            | 0.8038         | 0.7796     | 0.8081           |
+| 0.0199        | 44.0  | 220  | 1.1490          | {'precision': 0.7342342342342343, 'recall': 0.8059332509270705, 'f1': 0.7684148497348262, 'number': 809} | {'precision': 0.45255474452554745, 'recall': 0.5210084033613446, 'f1': 0.484375, 'number': 119}             | {'precision': 0.8126142595978062, 'recall': 0.8347417840375587, 'f1': 0.823529411764706, 'number': 1065}  | 0.7565            | 0.8043         | 0.7797     | 0.8075           |
+| 0.0209        | 45.0  | 225  | 1.1480          | {'precision': 0.7400228050171037, 'recall': 0.8022249690976514, 'f1': 0.7698695136417556, 'number': 809} | {'precision': 0.43448275862068964, 'recall': 0.5294117647058824, 'f1': 0.47727272727272724, 'number': 119}  | {'precision': 0.8106617647058824, 'recall': 0.828169014084507, 'f1': 0.819321876451463, 'number': 1065}   | 0.7555            | 0.7998         | 0.7770     | 0.8082           |
+| 0.02          | 46.0  | 230  | 1.1426          | {'precision': 0.7396788990825688, 'recall': 0.7972805933250927, 'f1': 0.7674003569303985, 'number': 809} | {'precision': 0.4405594405594406, 'recall': 0.5294117647058824, 'f1': 0.48091603053435117, 'number': 119}   | {'precision': 0.8108356290174472, 'recall': 0.8291079812206573, 'f1': 0.819870009285051, 'number': 1065}  | 0.7562            | 0.7983         | 0.7767     | 0.8085           |
+| 0.0186        | 47.0  | 235  | 1.1439          | {'precision': 0.738831615120275, 'recall': 0.7972805933250927, 'f1': 0.7669441141498216, 'number': 809}  | {'precision': 0.4405594405594406, 'recall': 0.5294117647058824, 'f1': 0.48091603053435117, 'number': 119}   | {'precision': 0.8110091743119267, 'recall': 0.8300469483568075, 'f1': 0.8204176334106729, 'number': 1065} | 0.7559            | 0.7988         | 0.7768     | 0.8090           |
+| 0.0212        | 48.0  | 240  | 1.1467          | {'precision': 0.736540664375716, 'recall': 0.7948084054388134, 'f1': 0.7645659928656362, 'number': 809}  | {'precision': 0.45323741007194246, 'recall': 0.5294117647058824, 'f1': 0.48837209302325585, 'number': 119}  | {'precision': 0.8115279048490394, 'recall': 0.8328638497652582, 'f1': 0.8220574606116775, 'number': 1065} | 0.7568            | 0.7993         | 0.7775     | 0.8092           |
+| 0.0212        | 49.0  | 245  | 1.1469          | {'precision': 0.7405281285878301, 'recall': 0.7972805933250927, 'f1': 0.7678571428571428, 'number': 809} | {'precision': 0.45323741007194246, 'recall': 0.5294117647058824, 'f1': 0.48837209302325585, 'number': 119}  | {'precision': 0.8115279048490394, 'recall': 0.8328638497652582, 'f1': 0.8220574606116775, 'number': 1065} | 0.7584            | 0.8003         | 0.7788     | 0.8098           |
+| 0.0179        | 50.0  | 250  | 1.1469          | {'precision': 0.7396788990825688, 'recall': 0.7972805933250927, 'f1': 0.7674003569303985, 'number': 809} | {'precision': 0.45323741007194246, 'recall': 0.5294117647058824, 'f1': 0.48837209302325585, 'number': 119}  | {'precision': 0.8115279048490394, 'recall': 0.8328638497652582, 'f1': 0.8220574606116775, 'number': 1065} | 0.7581            | 0.8003         | 0.7786     | 0.8101           |
+
+
+### Framework versions
+
+- Transformers 4.47.0
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0

logs/events.out.tfevents.1739170446.14fafa8eef2d.121.1

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preprocessor_config.json

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+{
+  "apply_ocr": true,
+  "do_resize": true,
+  "image_processor_type": "LayoutLMv2ImageProcessor",
+  "ocr_lang": null,
+  "processor_class": "LayoutLMv2Processor",
+  "resample": 2,
+  "size": {
+    "height": 224,
+    "width": 224
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+  "tesseract_config": ""
+}

special_tokens_map.json

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+{
+  "cls_token": {
+    "content": "[CLS]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+  "mask_token": {
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+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+  "pad_token": {
+    "content": "[PAD]",
+    "lstrip": false,
+    "normalized": false,
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+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
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+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "extra_special_tokens": {},
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "never_split": null,
+  "only_label_first_subword": true,
+  "pad_token": "[PAD]",
+  "pad_token_box": [
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+  "pad_token_label": -100,
+  "processor_class": "LayoutLMv2Processor",
+  "sep_token": "[SEP]",
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+    1000,
+    1000
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+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "LayoutLMv2Tokenizer",
+  "unk_token": "[UNK]"
+}