Training fold 1

README.md

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+---
+license: mit
+base_model: ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: best_berita_roberta_model_fold_1
+  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. -->
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>]()
+# best_berita_roberta_model_fold_1
+
+This model is a fine-tuned version of [ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa](https://huggingface.co/ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0964
+- Accuracy: 0.9817
+- Precision: 0.9812
+- Recall: 0.9826
+- F1: 0.9818
+
+## 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: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.6034        | 1.0   | 601  | 0.5137          | 0.8785   | 0.9043    | 0.8684 | 0.8758 |
+| 0.2584        | 2.0   | 1202 | 0.2616          | 0.9434   | 0.9438    | 0.9489 | 0.9435 |
+| 0.1286        | 3.0   | 1803 | 0.2470          | 0.9642   | 0.9645    | 0.9668 | 0.9646 |
+| 0.0948        | 4.0   | 2404 | 0.0964          | 0.9817   | 0.9812    | 0.9826 | 0.9818 |
+| 0.0405        | 5.0   | 3005 | 0.3506          | 0.9551   | 0.9560    | 0.9593 | 0.9558 |
+| 0.0038        | 6.0   | 3606 | 0.3762          | 0.9551   | 0.9549    | 0.9597 | 0.9551 |
+| 0.0105        | 7.0   | 4207 | 0.2738          | 0.9667   | 0.9657    | 0.9698 | 0.9666 |
+| 0.0004        | 8.0   | 4808 | 0.2319          | 0.9742   | 0.9732    | 0.9765 | 0.9743 |
+| 0.0018        | 9.0   | 5409 | 0.2551          | 0.9725   | 0.9715    | 0.9750 | 0.9726 |
+| 0.0           | 10.0  | 6010 | 0.2604          | 0.9725   | 0.9715    | 0.9750 | 0.9726 |
+
+
+### Framework versions
+
+- Transformers 4.42.3
+- Pytorch 2.1.2
+- Datasets 2.20.0
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa",
+  "architectures": [
+    "RobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "POSITIVE",
+    "1": "NEUTRAL",
+    "2": "NEGATIVE"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "NEGATIVE": 2,
+    "NEUTRAL": 1,
+    "POSITIVE": 0
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.42.3",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 50265
+}

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training_args.bin

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