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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: lxyuan/distilbert-base-multilingual-cased-sentiments-student
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - indonlu
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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: sentiment2
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+ results:
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+ - task:
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+ name: Text Classification
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+ type: text-classification
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+ dataset:
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+ name: indonlu
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+ type: indonlu
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+ config: smsa
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+ split: validation
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+ args: smsa
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.915079365079365
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+ - name: Precision
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+ type: precision
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+ value: 0.9152979362942885
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+ - name: Recall
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+ type: recall
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+ value: 0.915079365079365
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+ - name: F1
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+ type: f1
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+ value: 0.9149940431800128
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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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+ # sentiment2
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+
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+ This model is a fine-tuned version of [lxyuan/distilbert-base-multilingual-cased-sentiments-student](https://huggingface.co/lxyuan/distilbert-base-multilingual-cased-sentiments-student) on the indonlu dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6085
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+ - Accuracy: 0.9151
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+ - Precision: 0.9153
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+ - Recall: 0.9151
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+ - F1: 0.9150
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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: 40
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+ - eval_batch_size: 40
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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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+ - lr_scheduler_warmup_ratio: 0.01
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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 | 275 | 0.2543 | 0.9190 | 0.9213 | 0.9190 | 0.9196 |
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+ | 0.2191 | 2.0 | 550 | 0.2710 | 0.9143 | 0.9133 | 0.9143 | 0.9134 |
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+ | 0.2191 | 3.0 | 825 | 0.3715 | 0.9135 | 0.9144 | 0.9135 | 0.9114 |
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+ | 0.0714 | 4.0 | 1100 | 0.4751 | 0.9071 | 0.9085 | 0.9071 | 0.9077 |
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+ | 0.0714 | 5.0 | 1375 | 0.4859 | 0.9206 | 0.9214 | 0.9206 | 0.9203 |
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+ | 0.0263 | 6.0 | 1650 | 0.5383 | 0.9143 | 0.9155 | 0.9143 | 0.9143 |
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+ | 0.0263 | 7.0 | 1925 | 0.5630 | 0.9167 | 0.9166 | 0.9167 | 0.9165 |
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+ | 0.0126 | 8.0 | 2200 | 0.5916 | 0.9151 | 0.9151 | 0.9151 | 0.9146 |
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+ | 0.0126 | 9.0 | 2475 | 0.6073 | 0.9135 | 0.9130 | 0.9135 | 0.9131 |
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+ | 0.0056 | 10.0 | 2750 | 0.6085 | 0.9151 | 0.9153 | 0.9151 | 0.9150 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.17.1
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+ - Tokenizers 0.15.2
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