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README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.7614678899082569
+      value: 0.7189602446483181
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on the GLUE BOOLQ dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.4013
-- Accuracy: 0.7615
+- Loss: 1.4813
+- Accuracy: 0.7190
 
 ## Model description
 

all_results.json

@@ -1,14 +1,14 @@
 {
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     "eval_samples": 3270,
-    "eval_samples_per_second": 172.338,
-    "eval_steps_per_second": 21.555,
-    "train_loss": 0.2978504161511437,
-    "train_runtime": 903.0769,
+    "eval_samples_per_second": 385.11,
+    "eval_steps_per_second": 48.168,
+    "train_loss": 0.4028913801807468,
+    "train_runtime": 280.0096,
     "train_samples": 9427,
-    "train_samples_per_second": 52.194,
-    "train_steps_per_second": 3.267
+    "train_samples_per_second": 168.334,
+    "train_steps_per_second": 10.535
 }

eval_results.json

@@ -1,9 +1,9 @@
 {
     "epoch": 5.0,
-    "eval_accuracy": 0.7614678899082569,
-    "eval_loss": 1.4013047218322754,
-    "eval_runtime": 18.9743,
+    "eval_accuracy": 0.7189602446483181,
+    "eval_loss": 1.4812861680984497,
+    "eval_runtime": 8.4911,
     "eval_samples": 3270,
-    "eval_samples_per_second": 172.338,
-    "eval_steps_per_second": 21.555
+    "eval_samples_per_second": 385.11,
+    "eval_steps_per_second": 48.168
 }

pytorch_model.bin

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train_results.json

@@ -1,8 +1,8 @@
 {
     "epoch": 5.0,
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     "train_samples": 9427,
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-    "train_steps_per_second": 3.267
+    "train_samples_per_second": 168.334,
+    "train_steps_per_second": 10.535
 }

trainer_state.json

@@ -9,42 +9,42 @@
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       "step": 500
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training_args.bin

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