Model save

README.md

@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [indobenchmark/indobert-base-p1](https://huggingface.co/indobenchmark/indobert-base-p1) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.4057
-- Accuracy: 0.8875
-- Precision: 0.8875
-- Recall: 0.8875
-- F1: 0.8875
+- Loss: 0.3735
+- Accuracy: 0.9187
+- Precision: 0.9187
+- Recall: 0.9187
+- F1: 0.9187
 
 ## Model description
 
@@ -55,13 +55,13 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
-| No log        | 1.0   | 81   | 0.3598          | 0.875    | 0.875     | 0.875  | 0.875  |
-| No log        | 2.0   | 162  | 0.4057          | 0.8875   | 0.8875    | 0.8875 | 0.8875 |
+| No log        | 1.0   | 81   | 0.3478          | 0.8688   | 0.8688    | 0.8688 | 0.8688 |
+| No log        | 2.0   | 162  | 0.3735          | 0.9187   | 0.9187    | 0.9187 | 0.9187 |
 
 
 ### Framework versions
 
-- Transformers 4.40.2
+- Transformers 4.41.0
 - Pytorch 2.3.0+cu121
 - Datasets 2.19.1
 - Tokenizers 0.19.1

config.json

@@ -35,7 +35,7 @@
   "position_embedding_type": "absolute",
   "problem_type": "single_label_classification",
   "torch_dtype": "float32",
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+  "transformers_version": "4.41.0",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 50000

model.safetensors

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training_args.bin

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