End of training

README.md

@@ -15,14 +15,14 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-base-uncased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.5509
--  : {'precision': 0.3076923076923077, 'recall': 0.36363636363636365, 'f1': 0.33333333333333337, 'number': 22}
-- C: {'precision': 0.26666666666666666, 'recall': 0.34285714285714286, 'f1': 0.3, 'number': 35}
-- H: {'precision': 0.4074074074074074, 'recall': 0.4230769230769231, 'f1': 0.4150943396226415, 'number': 26}
-- Overall Precision: 0.3163
-- Overall Recall: 0.3735
-- Overall F1: 0.3425
-- Overall Accuracy: 0.8835
+- Loss: 0.5985
+-  : {'precision': 0.17391304347826086, 'recall': 0.18181818181818182, 'f1': 0.17777777777777776, 'number': 22}
+- C: {'precision': 0.20408163265306123, 'recall': 0.2857142857142857, 'f1': 0.23809523809523808, 'number': 35}
+- H: {'precision': 0.41935483870967744, 'recall': 0.5, 'f1': 0.45614035087719296, 'number': 26}
+- Overall Precision: 0.2621
+- Overall Recall: 0.3253
+- Overall F1: 0.2903
+- Overall Accuracy: 0.8694
 
 ## Model description
 
@@ -51,23 +51,23 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss |                                                                                                               | C                                                                                                           | H                                                                                                          | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:-------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
-| 1.2408        | 1.0   | 2    | 0.9939          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 22}                                                    | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 35}                                                  | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26}                                                 | 0.0               | 0.0            | 0.0        | 0.8182           |
-| 0.6685        | 2.0   | 4    | 0.8477          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 22}                                                    | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 35}                                                  | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26}                                                 | 0.0               | 0.0            | 0.0        | 0.8182           |
-| 0.5229        | 3.0   | 6    | 0.7519          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 22}                                                    | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 35}                                                  | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26}                                                 | 0.0               | 0.0            | 0.0        | 0.8182           |
-| 0.4147        | 4.0   | 8    | 0.6701          | {'precision': 0.045454545454545456, 'recall': 0.045454545454545456, 'f1': 0.045454545454545456, 'number': 22} | {'precision': 0.045454545454545456, 'recall': 0.02857142857142857, 'f1': 0.03508771929824561, 'number': 35} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26}                                                 | 0.0455            | 0.0241         | 0.0315     | 0.8464           |
-| 0.2847        | 5.0   | 10   | 0.6154          | {'precision': 0.125, 'recall': 0.13636363636363635, 'f1': 0.13043478260869565, 'number': 22}                  | {'precision': 0.041666666666666664, 'recall': 0.02857142857142857, 'f1': 0.03389830508474576, 'number': 35} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26}                                                 | 0.0833            | 0.0482         | 0.0611     | 0.8643           |
-| 0.2597        | 6.0   | 12   | 0.5752          | {'precision': 0.034482758620689655, 'recall': 0.045454545454545456, 'f1': 0.0392156862745098, 'number': 22}   | {'precision': 0.06896551724137931, 'recall': 0.05714285714285714, 'f1': 0.0625, 'number': 35}               | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26}                                                 | 0.0517            | 0.0361         | 0.0426     | 0.8668           |
-| 0.3162        | 7.0   | 14   | 0.6510          | {'precision': 0.15789473684210525, 'recall': 0.13636363636363635, 'f1': 0.14634146341463414, 'number': 22}    | {'precision': 0.09523809523809523, 'recall': 0.05714285714285714, 'f1': 0.07142857142857142, 'number': 35}  | {'precision': 0.5, 'recall': 0.038461538461538464, 'f1': 0.07142857142857144, 'number': 26}                | 0.1429            | 0.0723         | 0.0960     | 0.8399           |
-| 0.3601        | 8.0   | 16   | 0.6555          | {'precision': 0.13636363636363635, 'recall': 0.13636363636363635, 'f1': 0.13636363636363635, 'number': 22}    | {'precision': 0.07692307692307693, 'recall': 0.05714285714285714, 'f1': 0.06557377049180328, 'number': 35}  | {'precision': 0.6, 'recall': 0.11538461538461539, 'f1': 0.1935483870967742, 'number': 26}                  | 0.1509            | 0.0964         | 0.1176     | 0.8438           |
-| 0.3773        | 9.0   | 18   | 0.5827          | {'precision': 0.125, 'recall': 0.13636363636363635, 'f1': 0.13043478260869565, 'number': 22}                  | {'precision': 0.125, 'recall': 0.11428571428571428, 'f1': 0.11940298507462688, 'number': 35}                | {'precision': 0.6363636363636364, 'recall': 0.2692307692307692, 'f1': 0.37837837837837834, 'number': 26}   | 0.2090            | 0.1687         | 0.1867     | 0.8681           |
-| 0.2094        | 10.0  | 20   | 0.5452          | {'precision': 0.25, 'recall': 0.2727272727272727, 'f1': 0.2608695652173913, 'number': 22}                     | {'precision': 0.2571428571428571, 'recall': 0.2571428571428571, 'f1': 0.2571428571428571, 'number': 35}     | {'precision': 0.625, 'recall': 0.38461538461538464, 'f1': 0.4761904761904762, 'number': 26}                | 0.3333            | 0.3012         | 0.3165     | 0.8899           |
-| 0.1932        | 11.0  | 22   | 0.5436          | {'precision': 0.23076923076923078, 'recall': 0.2727272727272727, 'f1': 0.24999999999999994, 'number': 22}     | {'precision': 0.23076923076923078, 'recall': 0.2571428571428571, 'f1': 0.24324324324324323, 'number': 35}   | {'precision': 0.47368421052631576, 'recall': 0.34615384615384615, 'f1': 0.39999999999999997, 'number': 26} | 0.2857            | 0.2892         | 0.2874     | 0.8848           |
-| 0.1774        | 12.0  | 24   | 0.5541          | {'precision': 0.2916666666666667, 'recall': 0.3181818181818182, 'f1': 0.30434782608695654, 'number': 22}      | {'precision': 0.2682926829268293, 'recall': 0.3142857142857143, 'f1': 0.2894736842105263, 'number': 35}     | {'precision': 0.4782608695652174, 'recall': 0.4230769230769231, 'f1': 0.44897959183673475, 'number': 26}   | 0.3295            | 0.3494         | 0.3392     | 0.8835           |
-| 0.159         | 13.0  | 26   | 0.5567          | {'precision': 0.32, 'recall': 0.36363636363636365, 'f1': 0.3404255319148936, 'number': 22}                    | {'precision': 0.2857142857142857, 'recall': 0.34285714285714286, 'f1': 0.3116883116883117, 'number': 35}    | {'precision': 0.5217391304347826, 'recall': 0.46153846153846156, 'f1': 0.4897959183673469, 'number': 26}   | 0.3556            | 0.3855         | 0.3699     | 0.8835           |
-| 0.1623        | 14.0  | 28   | 0.5543          | {'precision': 0.32, 'recall': 0.36363636363636365, 'f1': 0.3404255319148936, 'number': 22}                    | {'precision': 0.3023255813953488, 'recall': 0.37142857142857144, 'f1': 0.3333333333333333, 'number': 35}    | {'precision': 0.46153846153846156, 'recall': 0.46153846153846156, 'f1': 0.46153846153846156, 'number': 26} | 0.3511            | 0.3976         | 0.3729     | 0.8860           |
-| 0.2053        | 15.0  | 30   | 0.5509          | {'precision': 0.3076923076923077, 'recall': 0.36363636363636365, 'f1': 0.33333333333333337, 'number': 22}     | {'precision': 0.26666666666666666, 'recall': 0.34285714285714286, 'f1': 0.3, 'number': 35}                  | {'precision': 0.4074074074074074, 'recall': 0.4230769230769231, 'f1': 0.4150943396226415, 'number': 26}    | 0.3163            | 0.3735         | 0.3425     | 0.8835           |
+| Training Loss | Epoch | Step | Validation Loss |                                                                                                               | C                                                                                                           | H                                                                                                         | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:-------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
+| 1.3414        | 1.0   | 2    | 0.9941          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 22}                                                    | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 35}                                                  | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26}                                                | 0.0               | 0.0            | 0.0        | 0.8182           |
+| 0.6808        | 2.0   | 4    | 0.8831          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 22}                                                    | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 35}                                                  | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26}                                                | 0.0               | 0.0            | 0.0        | 0.8182           |
+| 0.5134        | 3.0   | 6    | 0.7517          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 22}                                                    | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 35}                                                  | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26}                                                | 0.0               | 0.0            | 0.0        | 0.8182           |
+| 0.4175        | 4.0   | 8    | 0.6992          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 22}                                                    | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 35}                                                  | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26}                                                | 0.0               | 0.0            | 0.0        | 0.8182           |
+| 0.3048        | 5.0   | 10   | 0.6476          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 22}                                                    | {'precision': 0.13333333333333333, 'recall': 0.05714285714285714, 'f1': 0.08, 'number': 35}                 | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26}                                                | 0.0667            | 0.0241         | 0.0354     | 0.8310           |
+| 0.2767        | 6.0   | 12   | 0.6375          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 22}                                                    | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 35}                                                  | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26}                                                | 0.0               | 0.0            | 0.0        | 0.8399           |
+| 0.3514        | 7.0   | 14   | 0.6033          | {'precision': 0.047619047619047616, 'recall': 0.045454545454545456, 'f1': 0.046511627906976744, 'number': 22} | {'precision': 0.047619047619047616, 'recall': 0.02857142857142857, 'f1': 0.03571428571428571, 'number': 35} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26}                                                | 0.0476            | 0.0241         | 0.032      | 0.8656           |
+| 0.3766        | 8.0   | 16   | 0.6462          | {'precision': 0.13333333333333333, 'recall': 0.09090909090909091, 'f1': 0.10810810810810811, 'number': 22}    | {'precision': 0.06666666666666667, 'recall': 0.02857142857142857, 'f1': 0.04, 'number': 35}                 | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26}                                                | 0.1               | 0.0361         | 0.0531     | 0.8271           |
+| 0.4447        | 9.0   | 18   | 0.6570          | {'precision': 0.06666666666666667, 'recall': 0.045454545454545456, 'f1': 0.05405405405405406, 'number': 22}   | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 35}                                                  | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26}                                                | 0.0333            | 0.0120         | 0.0177     | 0.8182           |
+| 0.2359        | 10.0  | 20   | 0.6297          | {'precision': 0.15, 'recall': 0.13636363636363635, 'f1': 0.14285714285714282, 'number': 22}                   | {'precision': 0.08333333333333333, 'recall': 0.05714285714285714, 'f1': 0.06779661016949153, 'number': 35}  | {'precision': 0.5, 'recall': 0.07692307692307693, 'f1': 0.13333333333333336, 'number': 26}                | 0.1458            | 0.0843         | 0.1069     | 0.8438           |
+| 0.2136        | 11.0  | 22   | 0.6072          | {'precision': 0.20833333333333334, 'recall': 0.22727272727272727, 'f1': 0.21739130434782608, 'number': 22}    | {'precision': 0.16666666666666666, 'recall': 0.17142857142857143, 'f1': 0.16901408450704225, 'number': 35}  | {'precision': 0.42857142857142855, 'recall': 0.23076923076923078, 'f1': 0.3, 'number': 26}                | 0.2297            | 0.2048         | 0.2166     | 0.8617           |
+| 0.2114        | 12.0  | 24   | 0.5978          | {'precision': 0.17391304347826086, 'recall': 0.18181818181818182, 'f1': 0.17777777777777776, 'number': 22}    | {'precision': 0.1951219512195122, 'recall': 0.22857142857142856, 'f1': 0.21052631578947367, 'number': 35}   | {'precision': 0.4090909090909091, 'recall': 0.34615384615384615, 'f1': 0.37500000000000006, 'number': 26} | 0.2442            | 0.2530         | 0.2485     | 0.8656           |
+| 0.1826        | 13.0  | 26   | 0.5982          | {'precision': 0.17391304347826086, 'recall': 0.18181818181818182, 'f1': 0.17777777777777776, 'number': 22}    | {'precision': 0.18181818181818182, 'recall': 0.22857142857142856, 'f1': 0.20253164556962025, 'number': 35}  | {'precision': 0.4230769230769231, 'recall': 0.4230769230769231, 'f1': 0.4230769230769231, 'number': 26}   | 0.2473            | 0.2771         | 0.2614     | 0.8668           |
+| 0.1861        | 14.0  | 28   | 0.5983          | {'precision': 0.17391304347826086, 'recall': 0.18181818181818182, 'f1': 0.17777777777777776, 'number': 22}    | {'precision': 0.21739130434782608, 'recall': 0.2857142857142857, 'f1': 0.24691358024691357, 'number': 35}   | {'precision': 0.4642857142857143, 'recall': 0.5, 'f1': 0.4814814814814815, 'number': 26}                  | 0.2784            | 0.3253         | 0.3000     | 0.8707           |
+| 0.2442        | 15.0  | 30   | 0.5985          | {'precision': 0.17391304347826086, 'recall': 0.18181818181818182, 'f1': 0.17777777777777776, 'number': 22}    | {'precision': 0.20408163265306123, 'recall': 0.2857142857142857, 'f1': 0.23809523809523808, 'number': 35}   | {'precision': 0.41935483870967744, 'recall': 0.5, 'f1': 0.45614035087719296, 'number': 26}                | 0.2621            | 0.3253         | 0.2903     | 0.8694           |
 
 
 ### Framework versions

logs/events.out.tfevents.1711206742.ethanmbp.lan.34423.0

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:40aa2d31a9f37b9506d52442893b90490c2f4f3fa6118da5aa8556dbd373a762
-size 5414
+oid sha256:4dd1690302c8cf0e618e67ea0050ba7cdade6a13b84f09d323765666fa11464f
+size 15590

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ff381db291e27c638b6e3dd7ab1bcc4eb205c5625cb54d72c19718d2c6bf9cd4
+oid sha256:099bb93cfe5e201ed12dac7973bee497c7c6d011e6e4135fa217f500c0fcfcb9
 size 450552060

tokenizer.json

@@ -1,7 +1,21 @@
 {
   "version": "1.0",
-  "truncation": null,
-  "padding": null,
+  "truncation": {
+    "direction": "Right",
+    "max_length": 512,
+    "strategy": "LongestFirst",
+    "stride": 0
+  },
+  "padding": {
+    "strategy": {
+      "Fixed": 512
+    },
+    "direction": "Right",
+    "pad_to_multiple_of": null,
+    "pad_id": 0,
+    "pad_type_id": 0,
+    "pad_token": "[PAD]"
+  },
   "added_tokens": [
     {
       "id": 0,

tokenizer_config.json

@@ -54,11 +54,9 @@
   "do_basic_tokenize": true,
   "do_lower_case": true,
   "mask_token": "[MASK]",
-  "max_length": 512,
   "model_max_length": 512,
   "never_split": null,
   "only_label_first_subword": true,
-  "pad_to_multiple_of": null,
   "pad_token": "[PAD]",
   "pad_token_box": [
     0,
@@ -67,8 +65,6 @@
     0
   ],
   "pad_token_label": -100,
-  "pad_token_type_id": 0,
-  "padding_side": "right",
   "processor_class": "LayoutLMv2Processor",
   "sep_token": "[SEP]",
   "sep_token_box": [
@@ -77,11 +73,8 @@
     1000,
     1000
   ],
-  "stride": 0,
   "strip_accents": null,
   "tokenize_chinese_chars": true,
   "tokenizer_class": "LayoutLMv2Tokenizer",
-  "truncation_side": "right",
-  "truncation_strategy": "longest_first",
   "unk_token": "[UNK]"
 }