Model save

README.md

@@ -1,6 +1,6 @@
 ---
-license: apache-2.0
-base_model: indolem/indobertweet-base-uncased
+license: mit
+base_model: indobenchmark/indobert-base-p1
 tags:
 - generated_from_trainer
 metrics:
@@ -18,13 +18,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # kdrt_content
 
-This model is a fine-tuned version of [indolem/indobertweet-base-uncased](https://huggingface.co/indolem/indobertweet-base-uncased) on the None dataset.
+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: 0.0003
-- Accuracy: 1.0
-- Precision: 1.0
-- Recall: 1.0
-- F1: 1.0
+- Loss: 0.2446
+- Accuracy: 0.9231
+- Precision: 0.9231
+- Recall: 0.9231
+- F1: 0.9231
 
 ## Model description
 
@@ -53,15 +53,15 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1  |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:---:|
-| No log        | 1.0   | 101  | 0.0004          | 1.0      | 1.0       | 1.0    | 1.0 |
-| No log        | 2.0   | 202  | 0.0003          | 1.0      | 1.0       | 1.0    | 1.0 |
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| No log        | 1.0   | 59   | 0.4204          | 0.8291   | 0.8291    | 0.8291 | 0.8291 |
+| No log        | 2.0   | 118  | 0.2446          | 0.9231   | 0.9231    | 0.9231 | 0.9231 |
 
 
 ### Framework versions
 
-- Transformers 4.38.2
-- Pytorch 2.2.1+cu121
-- Datasets 2.18.0
-- Tokenizers 0.15.2
+- Transformers 4.40.0
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.0
+- Tokenizers 0.19.1

config.json

@@ -1,27 +1,24 @@
 {
-  "_name_or_path": "indolem/indobertweet-base-uncased",
+  "_name_or_path": "indobenchmark/indobert-base-p1",
+  "_num_labels": 5,
   "architectures": [
     "BertForSequenceClassification"
   ],
   "attention_probs_dropout_prob": 0.1,
-  "bos_token_id": 0,
   "classifier_dropout": null,
-  "eos_token_ids": 0,
-  "gradient_checkpointing": false,
+  "directionality": "bidi",
   "hidden_act": "gelu",
   "hidden_dropout_prob": 0.1,
   "hidden_size": 768,
   "id2label": {
-    "0": "negative",
-    "1": "neutral",
-    "2": "positive"
+    "0": "Negatif",
+    "1": "Positif"
   },
   "initializer_range": 0.02,
   "intermediate_size": 3072,
   "label2id": {
-    "negative": 0,
-    "neutral": 1,
-    "positive": 2
+    "Negatif": 0,
+    "Positif": 1
   },
   "layer_norm_eps": 1e-12,
   "max_position_embeddings": 512,
@@ -30,11 +27,16 @@
   "num_hidden_layers": 12,
   "output_past": true,
   "pad_token_id": 0,
+  "pooler_fc_size": 768,
+  "pooler_num_attention_heads": 12,
+  "pooler_num_fc_layers": 3,
+  "pooler_size_per_head": 128,
+  "pooler_type": "first_token_transform",
   "position_embedding_type": "absolute",
   "problem_type": "single_label_classification",
   "torch_dtype": "float32",
-  "transformers_version": "4.38.2",
+  "transformers_version": "4.40.0",
   "type_vocab_size": 2,
   "use_cache": true,
-  "vocab_size": 31923
+  "vocab_size": 50000
 }

model.safetensors

@@ -1,3 +1,3 @@
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+size 497795072

runs/Apr27_18-36-06_20581a7821f2/events.out.tfevents.1714242967.20581a7821f2.573.0

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runs/Apr27_18-36-06_20581a7821f2/events.out.tfevents.1714244474.20581a7821f2.573.1

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tokenizer_config.json

@@ -17,7 +17,7 @@
       "special": true
     },
     "2": {
-      "content": "[MASK]",
+      "content": "[CLS]",
       "lstrip": false,
       "normalized": false,
       "rstrip": false,
@@ -25,7 +25,7 @@
       "special": true
     },
     "3": {
-      "content": "[CLS]",
+      "content": "[SEP]",
       "lstrip": false,
       "normalized": false,
       "rstrip": false,
@@ -33,7 +33,7 @@
       "special": true
     },
     "4": {
-      "content": "[SEP]",
+      "content": "[MASK]",
       "lstrip": false,
       "normalized": false,
       "rstrip": false,

training_args.bin

@@ -1,3 +1,3 @@
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