End of training

README.md

@@ -23,10 +23,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.8733333333333333
+      value: 0.8833333333333333
     - name: F1
       type: f1
-      value: 0.8741721854304636
+      value: 0.8837209302325582
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -36,9 +36,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the imdb dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3396
-- Accuracy: 0.8733
-- F1: 0.8742
+- Loss: 0.3372
+- Accuracy: 0.8833
+- F1: 0.8837
 
 ## Model description
 
@@ -71,7 +71,7 @@ The following hyperparameters were used during training:
 
 ### Framework versions
 
-- Transformers 4.36.0.dev0
+- Transformers 4.35.2
 - Pytorch 2.1.0+cu118
 - Datasets 2.15.0
 - Tokenizers 0.15.0

config.json

@@ -20,7 +20,7 @@
   "position_embedding_type": "absolute",
   "problem_type": "single_label_classification",
   "torch_dtype": "float32",
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+  "transformers_version": "4.35.2",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 30522

model.safetensors

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training_args.bin

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