End of training

README.md

@@ -16,14 +16,14 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [SCUT-DLVCLab/lilt-roberta-en-base](https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base) on the funsd-layoutlmv3 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.4156
-- Answer: {'precision': 0.12441314553990611, 'recall': 0.19461444308445533, 'f1': 0.15178997613365156, 'number': 817}
+- Loss: 0.9729
+- Answer: {'precision': 0.5061511423550088, 'recall': 0.7050183598531212, 'f1': 0.5892583120204603, 'number': 817}
 - Header: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119}
-- Question: {'precision': 0.3996212121212121, 'recall': 0.3918291550603528, 'f1': 0.3956868260665729, 'number': 1077}
-- Overall Precision: 0.2489
-- Overall Recall: 0.2886
-- Overall F1: 0.2673
-- Overall Accuracy: 0.4746
+- Question: {'precision': 0.6674400618716164, 'recall': 0.8012999071494893, 'f1': 0.7282700421940929, 'number': 1077}
+- Overall Precision: 0.5840
+- Overall Recall: 0.7149
+- Overall F1: 0.6428
+- Overall Accuracy: 0.5953
 
 ## Model description
 
@@ -48,13 +48,14 @@ 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
-- training_steps: 20
+- training_steps: 40
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Answer                                                                                                      | Header                                                      | Question                                                                                                  | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:-----------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
-| 1.7056        | 0.27  | 20   | 1.4156          | {'precision': 0.12441314553990611, 'recall': 0.19461444308445533, 'f1': 0.15178997613365156, 'number': 817} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.3996212121212121, 'recall': 0.3918291550603528, 'f1': 0.3956868260665729, 'number': 1077} | 0.2489            | 0.2886         | 0.2673     | 0.4746           |
+| Training Loss | Epoch | Step | Validation Loss | Answer                                                                                                     | Header                                                      | Question                                                                                                  | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:----------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
+| 1.5938        | 0.27  | 20   | 1.1884          | {'precision': 0.3494347379239466, 'recall': 0.41615667074663404, 'f1': 0.37988826815642457, 'number': 817} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.4942455242966752, 'recall': 0.7177344475394615, 'f1': 0.5853843241196517, 'number': 1077} | 0.4387            | 0.5529         | 0.4892     | 0.5421           |
+| 1.1521        | 0.53  | 40   | 0.9729          | {'precision': 0.5061511423550088, 'recall': 0.7050183598531212, 'f1': 0.5892583120204603, 'number': 817}   | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.6674400618716164, 'recall': 0.8012999071494893, 'f1': 0.7282700421940929, 'number': 1077} | 0.5840            | 0.7149         | 0.6428     | 0.5953           |
 
 
 ### Framework versions

logs/events.out.tfevents.1677016282.c4ac2e57e392.8451.0

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-size 5547
+oid sha256:ffaaaf19eaeef1fcb8856f137e854ab87caf65a6ea09f6bc2eee4b1265b92807
+size 5895

logs/events.out.tfevents.1677017529.c4ac2e57e392.8451.2

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+size 583

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": 1,
+    "pad_type_id": 0,
+    "pad_token": "<pad>"
+  },
   "added_tokens": [
     {
       "id": 0,