End of training

README.md

@@ -1,4 +1,5 @@
 ---
+library_name: transformers
 base_model: layoutlmv3
 tags:
 - generated_from_trainer
@@ -21,16 +22,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.9435600578871202
+      value: 0.9515865227347072
     - name: Recall
       type: recall
-      value: 0.9421965317919075
+      value: 0.9645225464190982
     - name: F1
       type: f1
-      value: 0.9428778018799712
+      value: 0.9580108677753993
     - name: Accuracy
       type: accuracy
-      value: 0.9952312354080771
+      value: 0.9870755974971792
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -40,11 +41,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [layoutlmv3](https://huggingface.co/layoutlmv3) on the not-lain/sroie dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0319
-- Precision: 0.9436
-- Recall: 0.9422
-- F1: 0.9429
-- Accuracy: 0.9952
+- Loss: 0.0596
+- Precision: 0.9516
+- Recall: 0.9645
+- F1: 0.9580
+- Accuracy: 0.9871
 
 ## Model description
 
@@ -75,21 +76,21 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch   | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.5873  | 100  | 0.0429          | 0.8634    | 0.8772 | 0.8703 | 0.9896   |
-| No log        | 3.1746  | 200  | 0.0222          | 0.9079    | 0.9408 | 0.9241 | 0.9947   |
-| No log        | 4.7619  | 300  | 0.0285          | 0.9232    | 0.9379 | 0.9305 | 0.9939   |
-| No log        | 6.3492  | 400  | 0.0291          | 0.9393    | 0.9393 | 0.9393 | 0.9947   |
-| 0.0408        | 7.9365  | 500  | 0.0295          | 0.9223    | 0.9436 | 0.9329 | 0.9945   |
-| 0.0408        | 9.5238  | 600  | 0.0356          | 0.9223    | 0.9436 | 0.9329 | 0.9936   |
-| 0.0408        | 11.1111 | 700  | 0.0318          | 0.9397    | 0.9451 | 0.9424 | 0.9952   |
-| 0.0408        | 12.6984 | 800  | 0.0311          | 0.9312    | 0.9393 | 0.9353 | 0.9948   |
-| 0.0408        | 14.2857 | 900  | 0.0324          | 0.9394    | 0.9408 | 0.9401 | 0.9950   |
-| 0.0035        | 15.8730 | 1000 | 0.0319          | 0.9436    | 0.9422 | 0.9429 | 0.9952   |
+| No log        | 1.5873  | 100  | 0.0548          | 0.9415    | 0.9453 | 0.9434 | 0.9830   |
+| No log        | 3.1746  | 200  | 0.0531          | 0.9377    | 0.9625 | 0.9499 | 0.9847   |
+| No log        | 4.7619  | 300  | 0.0550          | 0.9414    | 0.9595 | 0.9504 | 0.9851   |
+| No log        | 6.3492  | 400  | 0.0560          | 0.9500    | 0.9645 | 0.9572 | 0.9868   |
+| 0.0464        | 7.9365  | 500  | 0.0596          | 0.9516    | 0.9645 | 0.9580 | 0.9871   |
+| 0.0464        | 9.5238  | 600  | 0.0630          | 0.9502    | 0.9622 | 0.9562 | 0.9865   |
+| 0.0464        | 11.1111 | 700  | 0.0707          | 0.9489    | 0.9658 | 0.9573 | 0.9868   |
+| 0.0464        | 12.6984 | 800  | 0.0726          | 0.9515    | 0.9629 | 0.9572 | 0.9868   |
+| 0.0464        | 14.2857 | 900  | 0.0765          | 0.9510    | 0.9652 | 0.9580 | 0.9871   |
+| 0.0048        | 15.8730 | 1000 | 0.0773          | 0.9500    | 0.9645 | 0.9572 | 0.9868   |
 
 
 ### Framework versions
 
-- Transformers 4.44.0
+- Transformers 4.44.2
 - Pytorch 2.4.0+cu118
-- Datasets 2.20.0
+- Datasets 2.21.0
 - Tokenizers 0.19.1

all_results.json

@@ -1,10 +1,10 @@
 {
-    "predict_accuracy": 0.995264637695457,
-    "predict_f1": 0.9448028673835126,
-    "predict_loss": 0.03440123423933983,
-    "predict_precision": 0.9427753934191703,
-    "predict_recall": 0.9468390804597702,
-    "predict_runtime": 14.7491,
-    "predict_samples_per_second": 11.797,
-    "predict_steps_per_second": 1.22
+    "predict_accuracy": 0.9890338907358706,
+    "predict_f1": 0.9620923688131104,
+    "predict_loss": 0.06438335031270981,
+    "predict_precision": 0.9600264288074001,
+    "predict_recall": 0.9641672196416722,
+    "predict_runtime": 15.9404,
+    "predict_samples_per_second": 10.916,
+    "predict_steps_per_second": 1.129
 }

model.safetensors

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 size 501349380

predict_results.json

@@ -1,10 +1,10 @@
 {
-    "predict_accuracy": 0.995264637695457,
-    "predict_f1": 0.9448028673835126,
-    "predict_loss": 0.03440123423933983,
-    "predict_precision": 0.9427753934191703,
-    "predict_recall": 0.9468390804597702,
-    "predict_runtime": 14.7491,
-    "predict_samples_per_second": 11.797,
-    "predict_steps_per_second": 1.22
+    "predict_accuracy": 0.9890338907358706,
+    "predict_f1": 0.9620923688131104,
+    "predict_loss": 0.06438335031270981,
+    "predict_precision": 0.9600264288074001,
+    "predict_recall": 0.9641672196416722,
+    "predict_runtime": 15.9404,
+    "predict_samples_per_second": 10.916,
+    "predict_steps_per_second": 1.129
 }

runs/Aug26_23-30-18_bernini/events.out.tfevents.1724709196.bernini.20168.1

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+size 560