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Training fold 1

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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ - precision
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+ - recall
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+ - f1
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+ model-index:
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+ - name: 22best_berita_roberta_model_fold_1
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>]()
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+ [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>]()
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+ # 22best_berita_roberta_model_fold_1
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+
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+ 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.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8575
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+ - Accuracy: 0.8868
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+ - Precision: 0.8904
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+ - Recall: 0.8843
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+ - F1: 0.8870
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | No log | 1.0 | 106 | 0.9177 | 0.5472 | 0.7029 | 0.6055 | 0.5274 |
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+ | No log | 2.0 | 212 | 0.8990 | 0.7264 | 0.7612 | 0.7252 | 0.7101 |
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+ | No log | 3.0 | 318 | 0.7968 | 0.8491 | 0.8478 | 0.8622 | 0.8496 |
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+ | No log | 4.0 | 424 | 0.8026 | 0.8396 | 0.8400 | 0.8413 | 0.8353 |
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+ | 0.5042 | 5.0 | 530 | 1.0039 | 0.8443 | 0.8579 | 0.8603 | 0.8488 |
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+ | 0.5042 | 6.0 | 636 | 0.8274 | 0.8774 | 0.8743 | 0.8850 | 0.8780 |
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+ | 0.5042 | 7.0 | 742 | 0.8575 | 0.8868 | 0.8904 | 0.8843 | 0.8870 |
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+ | 0.5042 | 8.0 | 848 | 0.9014 | 0.8821 | 0.8806 | 0.8906 | 0.8830 |
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+ | 0.5042 | 9.0 | 954 | 0.9622 | 0.8726 | 0.8723 | 0.8859 | 0.8741 |
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+ | 0.0373 | 10.0 | 1060 | 0.9673 | 0.8726 | 0.8723 | 0.8859 | 0.8741 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.42.3
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+ - Pytorch 2.1.2
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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+ {
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+ "_name_or_path": "ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa",
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+ "architectures": [
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+ "RobertaForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "bos_token_id": 0,
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+ "classifier_dropout": null,
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+ "eos_token_id": 2,
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+ "gradient_checkpointing": false,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "POSITIVE",
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+ "1": "NEUTRAL",
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+ "2": "NEGATIVE"
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+ "NEUTRAL": 1,
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+ "POSITIVE": 0
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+ },
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+ "layer_norm_eps": 1e-05,
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+ "max_position_embeddings": 514,
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+ "model_type": "roberta",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 1,
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+ "position_embedding_type": "absolute",
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+ "problem_type": "single_label_classification",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.42.3",
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+ "type_vocab_size": 1,
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+ "use_cache": true,
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+ "vocab_size": 50265
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+ }
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