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--- |
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library_name: transformers |
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license: mit |
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base_model: w11wo/indonesian-roberta-base-sentiment-classifier |
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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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model-index: |
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- name: results_final |
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results: [] |
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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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# results_final |
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This model is a fine-tuned version of [w11wo/indonesian-roberta-base-sentiment-classifier](https://huggingface.co/w11wo/indonesian-roberta-base-sentiment-classifier) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0692 |
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- Accuracy: 0.8436 |
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- F1 Macro: 0.8431 |
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- F1 Weighted: 0.8433 |
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- Precision Macro: 0.8432 |
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- Recall Macro: 0.8434 |
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- Precision Weighted: 0.8433 |
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- Recall Weighted: 0.8436 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 8.879626978799419e-06 |
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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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted | Precision Macro | Recall Macro | Precision Weighted | Recall Weighted | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:-----------:|:---------------:|:------------:|:------------------:|:---------------:| |
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| 0.035 | 1.8182 | 500 | 1.0247 | 0.8327 | 0.8321 | 0.8323 | 0.8325 | 0.8325 | 0.8325 | 0.8327 | |
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| 0.0829 | 3.6364 | 1000 | 1.0134 | 0.8273 | 0.8262 | 0.8263 | 0.8275 | 0.8270 | 0.8275 | 0.8273 | |
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| 0.1858 | 5.4545 | 1500 | 1.0692 | 0.8436 | 0.8431 | 0.8433 | 0.8432 | 0.8434 | 0.8433 | 0.8436 | |
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| 0.2844 | 7.2727 | 2000 | 0.9823 | 0.8255 | 0.8250 | 0.8251 | 0.8253 | 0.8253 | 0.8254 | 0.8255 | |
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| 0.3299 | 9.0909 | 2500 | 0.9626 | 0.8255 | 0.8251 | 0.8252 | 0.8253 | 0.8253 | 0.8254 | 0.8255 | |
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### Framework versions |
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- Transformers 4.51.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 2.14.4 |
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- Tokenizers 0.21.1 |
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