End of training

README.md

@@ -1,14 +1,29 @@
 ---
 library_name: transformers
+language:
+- en
 license: apache-2.0
 base_model: google/bert_uncased_L-4_H-128_A-2
 tags:
 - generated_from_trainer
+datasets:
+- glue
 metrics:
 - accuracy
 model-index:
 - name: bert_uncased_L-4_H-128_A-2_wnli
-  results: []
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: GLUE WNLI
+      type: glue
+      args: wnli
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.352112676056338
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,10 +31,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # bert_uncased_L-4_H-128_A-2_wnli
 
-This model is a fine-tuned version of [google/bert_uncased_L-4_H-128_A-2](https://huggingface.co/google/bert_uncased_L-4_H-128_A-2) on an unknown dataset.
+This model is a fine-tuned version of [google/bert_uncased_L-4_H-128_A-2](https://huggingface.co/google/bert_uncased_L-4_H-128_A-2) on the GLUE WNLI dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.7140
-- Accuracy: 0.3239
+- Loss: 0.7042
+- Accuracy: 0.3521
 
 ## Model description
 

all_results.json

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+    "train_runtime": 3.1238,
+    "train_samples": 635,
+    "train_samples_per_second": 10163.884,
+    "train_steps_per_second": 48.018
+}

eval_results.json

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+{
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+    "eval_loss": 0.704170286655426,
+    "eval_runtime": 0.0335,
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+    "eval_steps_per_second": 29.808
+}

logs/events.out.tfevents.1733338908.ki-g0008.1764072.33

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+oid sha256:0a41a658bdb2de9bf3a3b72d3fb075550b35c8833cbbffc29578a64a907a0691
+size 405

train_results.json

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+    "train_steps_per_second": 48.018
+}

trainer_state.json

@@ -0,0 +1,163 @@
+{
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+  "best_model_checkpoint": "bert_uncased_L-4_H-128_A-2_wnli/checkpoint-6",
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+  "is_world_process_zero": true,
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+}