End of training

README.md

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+---
+license: mit
+base_model: indobenchmark/indobert-large-p2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+model-index:
+- name: wrete-indonlu
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# wrete-indonlu
+
+This model is a fine-tuned version of [indobenchmark/indobert-large-p2](https://huggingface.co/indobenchmark/indobert-large-p2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0433
+- Accuracy: 0.98
+- Precision: 0.98
+- Recall: 0.98
+- F1 Score: 0.9799
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-06
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 7
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
+| 0.1774        | 1.0   | 88   | 0.5232          | 0.92     | 0.92      | 0.92   | 0.9177   |
+| 0.0992        | 2.0   | 176  | 0.2976          | 0.94     | 0.94      | 0.94   | 0.9388   |
+| 0.0645        | 3.0   | 264  | 0.1118          | 0.98     | 0.98      | 0.98   | 0.9799   |
+| 0.029         | 4.0   | 352  | 0.1066          | 0.98     | 0.98      | 0.98   | 0.9799   |
+| 0.0333        | 5.0   | 440  | 0.0665          | 0.98     | 0.98      | 0.98   | 0.9799   |
+| 0.0153        | 6.0   | 528  | 0.0504          | 0.98     | 0.98      | 0.98   | 0.9799   |
+| 0.0092        | 7.0   | 616  | 0.0433          | 0.98     | 0.98      | 0.98   | 0.9799   |
+
+
+### Framework versions
+
+- Transformers 4.38.1
+- Pytorch 2.1.2
+- Datasets 2.1.0
+- Tokenizers 0.15.2

config.json

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+{
+  "_name_or_path": "indobenchmark/indobert-large-p2",
+  "_num_labels": 5,
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "directionality": "bidi",
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "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": "4.38.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

model.safetensors

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+size 1340622760

training_args.bin

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