Training fold 3

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: 22best_berita_roberta_model_fold_3
+  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"/>]()
+# 22best_berita_roberta_model_fold_3
+
+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: 0.9238
+- Accuracy: 0.8815
+- Precision: 0.8816
+- Recall: 0.8882
+- F1: 0.8802
+
+## 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     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| No log        | 1.0   | 106  | 0.4861          | 0.8009   | 0.8185    | 0.7929 | 0.7946 |
+| No log        | 2.0   | 212  | 0.6104          | 0.7820   | 0.8077    | 0.7810 | 0.7751 |
+| No log        | 3.0   | 318  | 0.6139          | 0.8246   | 0.8276    | 0.8147 | 0.8144 |
+| No log        | 4.0   | 424  | 1.1299          | 0.8294   | 0.8478    | 0.8432 | 0.8281 |
+| 0.4919        | 5.0   | 530  | 0.9623          | 0.8531   | 0.8547    | 0.8608 | 0.8511 |
+| 0.4919        | 6.0   | 636  | 0.8674          | 0.8768   | 0.8771    | 0.8825 | 0.8750 |
+| 0.4919        | 7.0   | 742  | 0.9238          | 0.8815   | 0.8816    | 0.8882 | 0.8802 |
+| 0.4919        | 8.0   | 848  | 0.9191          | 0.8673   | 0.8658    | 0.8712 | 0.8649 |
+| 0.4919        | 9.0   | 954  | 1.0218          | 0.8673   | 0.8681    | 0.8712 | 0.8647 |
+| 0.0165        | 10.0  | 1060 | 1.0294          | 0.8720   | 0.8725    | 0.8769 | 0.8699 |
+
+
+### 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
+}

model.safetensors

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runs/Jul17_17-51-26_f44a82bb8540/events.out.tfevents.1721238687.f44a82bb8540.34.0

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training_args.bin

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