End of training

README.md

@@ -11,21 +11,21 @@ should probably proofread and complete it, then remove this comment. -->
 
 # layoutlm-doclaynet-test
 
-This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-base-uncased) on an unknown dataset.
+This model is a fine-tuned version of [pmorelr/layoutlm-doclaynet-test](https://huggingface.co/pmorelr/layoutlm-doclaynet-test) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3457
-- Footer: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 256}
+- Loss: 0.1275
+- Footer: {'precision': 0.3970037453183521, 'recall': 0.4140625, 'f1': 0.40535372848948376, 'number': 256}
 - Header: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 95}
-- Able: {'precision': 0.043478260869565216, 'recall': 0.13671875, 'f1': 0.06597549481621112, 'number': 256}
+- Able: {'precision': 0.4575757575757576, 'recall': 0.58984375, 'f1': 0.515358361774744, 'number': 256}
 - Aption: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 64}
-- Ext: {'precision': 0.07320099255583126, 'recall': 0.12854030501089325, 'f1': 0.0932806324110672, 'number': 459}
-- Icture: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 49}
+- Ext: {'precision': 0.4011627906976744, 'recall': 0.45098039215686275, 'f1': 0.4246153846153846, 'number': 459}
+- Icture: {'precision': 0.1509433962264151, 'recall': 0.16326530612244897, 'f1': 0.15686274509803919, 'number': 49}
 - Itle: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 10}
 - Ootnote: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1}
-- Overall Precision: 0.0583
-- Overall Recall: 0.0790
-- Overall F1: 0.0671
-- Overall Accuracy: 0.9150
+- Overall Precision: 0.4034
+- Overall Recall: 0.3966
+- Overall F1: 0.4
+- Overall Accuracy: 0.9645
 
 ## Model description
 
@@ -50,13 +50,15 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 1
+- num_epochs: 3
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Footer                                                      | Header                                                     | Able                                                                                                | Aption                                                     | Ext                                                                                                        | Icture                                                     | Itle                                                       | Ootnote                                                   | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:-----------------------------------------------------------:|:----------------------------------------------------------:|:---------------------------------------------------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:---------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
-| 0.7273        | 1.0   | 43   | 0.3457          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 256} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 95} | {'precision': 0.043478260869565216, 'recall': 0.13671875, 'f1': 0.06597549481621112, 'number': 256} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 64} | {'precision': 0.07320099255583126, 'recall': 0.12854030501089325, 'f1': 0.0932806324110672, 'number': 459} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 49} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 10} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | 0.0583            | 0.0790         | 0.0671     | 0.9150           |
+| Training Loss | Epoch | Step | Validation Loss | Footer                                                                                           | Header                                                     | Able                                                                                               | Aption                                                     | Ext                                                                                                       | Icture                                                                                                    | Itle                                                       | Ootnote                                                   | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:------------------------------------------------------------------------------------------------:|:----------------------------------------------------------:|:--------------------------------------------------------------------------------------------------:|:----------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------:|:---------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
+| 0.3298        | 1.0   | 43   | 0.2178          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 256}                                      | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 95} | {'precision': 0.18888888888888888, 'recall': 0.33203125, 'f1': 0.24079320113314445, 'number': 256} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 64} | {'precision': 0.2778993435448578, 'recall': 0.2766884531590414, 'f1': 0.27729257641921395, 'number': 459} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 49}                                                | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 10} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | 0.2309            | 0.1782         | 0.2011     | 0.9419           |
+| 0.2034        | 2.0   | 86   | 0.1505          | {'precision': 0.4134078212290503, 'recall': 0.2890625, 'f1': 0.34022988505747126, 'number': 256} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 95} | {'precision': 0.3140495867768595, 'recall': 0.4453125, 'f1': 0.3683360258481421, 'number': 256}    | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 64} | {'precision': 0.36401673640167365, 'recall': 0.3790849673202614, 'f1': 0.3713980789754536, 'number': 459} | {'precision': 0.0625, 'recall': 0.061224489795918366, 'f1': 0.061855670103092786, 'number': 49}           | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 10} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | 0.3408            | 0.3067         | 0.3229     | 0.9579           |
+| 0.1584        | 3.0   | 129  | 0.1275          | {'precision': 0.3970037453183521, 'recall': 0.4140625, 'f1': 0.40535372848948376, 'number': 256} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 95} | {'precision': 0.4575757575757576, 'recall': 0.58984375, 'f1': 0.515358361774744, 'number': 256}    | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 64} | {'precision': 0.4011627906976744, 'recall': 0.45098039215686275, 'f1': 0.4246153846153846, 'number': 459} | {'precision': 0.1509433962264151, 'recall': 0.16326530612244897, 'f1': 0.15686274509803919, 'number': 49} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 10} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | 0.4034            | 0.3966         | 0.4        | 0.9645           |
 
 
 ### Framework versions

logs/events.out.tfevents.1678657976.Pedros-MacBook-Air.local.95418.2

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:a17b6860fecc895ac3620de82c19c0fbf146afd925c96888b54e05ac1d29f343
-size 6346
+oid sha256:506fd3d02768db0a59c8346f46e6438be1a97479bdf8b211d348595f6982ddd8
+size 6700

tokenizer.json

@@ -1,21 +1,7 @@
 {
   "version": "1.0",
-  "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]"
-  },
+  "truncation": null,
+  "padding": null,
   "added_tokens": [
     {
       "id": 0,

tokenizer_config.json

@@ -12,7 +12,7 @@
   "do_lower_case": true,
   "mask_token": "[MASK]",
   "model_max_length": 512,
-  "name_or_path": "microsoft/layoutlmv2-base-uncased",
+  "name_or_path": "pmorelr/layoutlm-doclaynet-test",
   "never_split": null,
   "only_label_first_subword": true,
   "pad_token": "[PAD]",