End of training

README.md

@@ -4,51 +4,28 @@ base_model: microsoft/layoutlmv3-base
 tags:
 - generated_from_trainer
 datasets:
-- funsd
-metrics:
-- precision
-- recall
-- f1
-- accuracy
+- generated
 model-index:
-- name: layoutlmv3-finetuned-funsd
-  results:
-  - task:
-      name: Token Classification
-      type: token-classification
-    dataset:
-      name: funsd
-      type: funsd
-      config: funsd
-      split: test
-      args: funsd
-    metrics:
-    - name: Precision
-      type: precision
-      value: 0.7467652495378928
-    - name: Recall
-      type: recall
-      value: 0.8027819175360159
-    - name: F1
-      type: f1
-      value: 0.7737610725401005
-    - name: Accuracy
-      type: accuracy
-      value: 0.8188517770117675
+- name: layoutlmv3-finetuned-invoice
+  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. -->
 
-# layoutlmv3-finetuned-funsd
+# layoutlmv3-finetuned-invoice
 
-This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the funsd dataset.
+This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the generated dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.5984
-- Precision: 0.7468
-- Recall: 0.8028
-- F1: 0.7738
-- Accuracy: 0.8189
+- eval_loss: 2.6166
+- eval_precision: 0.0108
+- eval_recall: 0.1034
+- eval_f1: 0.0195
+- eval_accuracy: 0.0116
+- eval_runtime: 31.3704
+- eval_samples_per_second: 1.594
+- eval_steps_per_second: 1.594
+- step: 0
 
 ## Model description
 
@@ -73,23 +50,7 @@ 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: 1000
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 0.67  | 100  | 1.0197          | 0.5025    | 0.5981 | 0.5462 | 0.6622   |
-| No log        | 1.34  | 200  | 0.6833          | 0.6203    | 0.7238 | 0.6680 | 0.7608   |
-| No log        | 2.01  | 300  | 0.6237          | 0.6401    | 0.7794 | 0.7030 | 0.7846   |
-| No log        | 2.68  | 400  | 0.6028          | 0.6892    | 0.7392 | 0.7133 | 0.7771   |
-| 0.8343        | 3.36  | 500  | 0.5948          | 0.7175    | 0.7884 | 0.7512 | 0.7991   |
-| 0.8343        | 4.03  | 600  | 0.5953          | 0.7135    | 0.8028 | 0.7555 | 0.7961   |
-| 0.8343        | 4.7   | 700  | 0.5925          | 0.7354    | 0.7953 | 0.7642 | 0.8174   |
-| 0.8343        | 5.37  | 800  | 0.6055          | 0.7397    | 0.7933 | 0.7656 | 0.8134   |
-| 0.8343        | 6.04  | 900  | 0.5940          | 0.7535    | 0.8077 | 0.7797 | 0.8199   |
-| 0.3468        | 6.71  | 1000 | 0.5984          | 0.7468    | 0.8028 | 0.7738 | 0.8189   |
-
+- training_steps: 2000
 
 ### Framework versions
 

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d2f9a6460545edb1fbd48ff4dd83587c71211b84a3dc007d23b1f515b7bea38b
+oid sha256:2b15d74c2da58a58eed5c3156d761613fc6a5847270d6270a20cb1a63586444d
 size 503782186

training_args.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ba1d3e10f06dcce028e49ac4cecd1142671a2caa391dfd9de37d544bfd3f9e4b
+oid sha256:593822fa6212d99046ed62692dc59a38d1a66c346de65d36cca71f17165c0765
 size 4536