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RoBERTa-Base-SE2025T11A-sun-v20241225073733

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  1. README.md +151 -0
  2. config.json +41 -0
  3. merges.txt +0 -0
  4. model.safetensors +3 -0
  5. runs/Dec25_07-37-59_4b45fc2a0861/events.out.tfevents.1735112282.4b45fc2a0861.2268.0 +3 -0
  6. special_tokens_map.json +51 -0
  7. tokenizer.json +0 -0
  8. tokenizer_config.json +58 -0
  9. training_args.bin +3 -0
  10. vocab.json +0 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: mit
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+ base_model: w11wo/sundanese-roberta-base-emotion-classifier
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: RoBERTa-Base-SE2025T11A-sun-v20241225073733
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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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+ # RoBERTa-Base-SE2025T11A-sun-v20241225073733
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+
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+ This model is a fine-tuned version of [w11wo/sundanese-roberta-base-emotion-classifier](https://huggingface.co/w11wo/sundanese-roberta-base-emotion-classifier) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5770
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+ - F1 Macro: 0.4036
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+ - F1 Micro: 0.6979
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+ - F1 Weighted: 0.6788
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+ - F1 Samples: 0.7240
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+ - F1 Label Marah: 0.3158
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+ - F1 Label Jijik: 0.4
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+ - F1 Label Takut: 0.0
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+ - F1 Label Senang: 0.8776
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+ - F1 Label Sedih: 0.7273
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+ - F1 Label Terkejut: 0.3043
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+ - F1 Label Biasa: 0.2
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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: 2e-05
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+ - train_batch_size: 2
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+ - eval_batch_size: 2
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+ - seed: 42
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+ - optimizer: Use 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: linear
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+ - num_epochs: 25
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Micro | F1 Weighted | F1 Samples | F1 Label Marah | F1 Label Jijik | F1 Label Takut | F1 Label Senang | F1 Label Sedih | F1 Label Terkejut | F1 Label Biasa |
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+ |:-------------:|:-------:|:----:|:---------------:|:--------:|:--------:|:-----------:|:----------:|:--------------:|:--------------:|:--------------:|:---------------:|:--------------:|:-----------------:|:--------------:|
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+ | 0.4233 | 0.2994 | 100 | 0.3265 | 0.1217 | 0.6312 | 0.4679 | 0.6615 | 0.0 | 0.0 | 0.0 | 0.8520 | 0.0 | 0.0 | 0.0 |
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+ | 0.4072 | 0.5988 | 200 | 0.2954 | 0.2063 | 0.6780 | 0.5708 | 0.6771 | 0.0 | 0.0 | 0.0 | 0.8788 | 0.5652 | 0.0 | 0.0 |
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+ | 0.3778 | 0.8982 | 300 | 0.2838 | 0.2633 | 0.6887 | 0.5790 | 0.7161 | 0.4444 | 0.0 | 0.0 | 0.8720 | 0.5263 | 0.0 | 0.0 |
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+ | 0.2968 | 1.1976 | 400 | 0.3056 | 0.3553 | 0.7055 | 0.6063 | 0.7292 | 0.5455 | 0.5 | 0.0 | 0.8774 | 0.5641 | 0.0 | 0.0 |
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+ | 0.3193 | 1.4970 | 500 | 0.2859 | 0.3452 | 0.6623 | 0.5986 | 0.6654 | 0.4706 | 0.4444 | 0.0 | 0.8457 | 0.6557 | 0.0 | 0.0 |
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+ | 0.308 | 1.7964 | 600 | 0.2684 | 0.3539 | 0.7086 | 0.6257 | 0.7240 | 0.4 | 0.5 | 0.0 | 0.8877 | 0.6897 | 0.0 | 0.0 |
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+ | 0.2574 | 2.0958 | 700 | 0.2980 | 0.3544 | 0.6993 | 0.6130 | 0.7234 | 0.5455 | 0.4444 | 0.0 | 0.8788 | 0.6122 | 0.0 | 0.0 |
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+ | 0.2352 | 2.3952 | 800 | 0.2827 | 0.3865 | 0.6965 | 0.6427 | 0.7117 | 0.5455 | 0.4444 | 0.0 | 0.8602 | 0.6885 | 0.1667 | 0.0 |
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+ | 0.2533 | 2.6946 | 900 | 0.2573 | 0.4206 | 0.7492 | 0.6959 | 0.7638 | 0.5455 | 0.4444 | 0.0 | 0.8980 | 0.8 | 0.2564 | 0.0 |
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+ | 0.2436 | 2.9940 | 1000 | 0.2990 | 0.3576 | 0.6769 | 0.6503 | 0.7013 | 0.4211 | 0.2857 | 0.0 | 0.8691 | 0.6667 | 0.2609 | 0.0 |
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+ | 0.179 | 3.2934 | 1100 | 0.2911 | 0.3428 | 0.6730 | 0.6307 | 0.6977 | 0.375 | 0.3333 | 0.0 | 0.8649 | 0.6552 | 0.1714 | 0.0 |
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+ | 0.1982 | 3.5928 | 1200 | 0.3006 | 0.3789 | 0.6951 | 0.6622 | 0.7172 | 0.4211 | 0.375 | 0.0 | 0.8691 | 0.7308 | 0.2564 | 0.0 |
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+ | 0.1744 | 3.8922 | 1300 | 0.3002 | 0.3791 | 0.7015 | 0.6571 | 0.7169 | 0.4615 | 0.3636 | 0.0 | 0.8643 | 0.72 | 0.2439 | 0.0 |
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+ | 0.1464 | 4.1916 | 1400 | 0.3178 | 0.3823 | 0.7032 | 0.6427 | 0.7146 | 0.5455 | 0.4444 | 0.0 | 0.8731 | 0.6957 | 0.1176 | 0.0 |
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+ | 0.136 | 4.4910 | 1500 | 0.3143 | 0.3620 | 0.7107 | 0.6619 | 0.7266 | 0.4 | 0.25 | 0.0 | 0.8673 | 0.7170 | 0.3 | 0.0 |
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+ | 0.1258 | 4.7904 | 1600 | 0.3286 | 0.4306 | 0.7021 | 0.6939 | 0.7208 | 0.4211 | 0.25 | 0.0 | 0.8705 | 0.7755 | 0.3333 | 0.3636 |
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+ | 0.1144 | 5.0898 | 1700 | 0.3240 | 0.4429 | 0.7152 | 0.6865 | 0.7339 | 0.375 | 0.4444 | 0.0 | 0.8687 | 0.7755 | 0.2727 | 0.3636 |
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+ | 0.0899 | 5.3892 | 1800 | 0.3375 | 0.4518 | 0.7256 | 0.6901 | 0.7427 | 0.4615 | 0.4444 | 0.0 | 0.8687 | 0.7547 | 0.3 | 0.3333 |
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+ | 0.0959 | 5.6886 | 1900 | 0.3258 | 0.4375 | 0.7323 | 0.6995 | 0.7432 | 0.4615 | 0.25 | 0.0 | 0.8776 | 0.7843 | 0.3256 | 0.3636 |
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+ | 0.0934 | 5.9880 | 2000 | 0.3437 | 0.4257 | 0.7055 | 0.6789 | 0.7240 | 0.4 | 0.3333 | 0.0 | 0.8586 | 0.7547 | 0.3 | 0.3333 |
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+ | 0.0713 | 6.2874 | 2100 | 0.3629 | 0.4337 | 0.6977 | 0.6919 | 0.7195 | 0.3333 | 0.3636 | 0.0 | 0.8660 | 0.7170 | 0.3922 | 0.3636 |
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+ | 0.0584 | 6.5868 | 2200 | 0.3695 | 0.4064 | 0.6982 | 0.6751 | 0.7180 | 0.4211 | 0.3636 | 0.0 | 0.875 | 0.7368 | 0.2667 | 0.1818 |
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+ | 0.059 | 6.8862 | 2300 | 0.3909 | 0.3894 | 0.7126 | 0.6848 | 0.7333 | 0.375 | 0.3636 | 0.0 | 0.8780 | 0.7692 | 0.3396 | 0.0 |
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+ | 0.0586 | 7.1856 | 2400 | 0.3815 | 0.4200 | 0.7025 | 0.6931 | 0.7263 | 0.375 | 0.4 | 0.0 | 0.8856 | 0.7778 | 0.3019 | 0.2 |
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+ | 0.0314 | 7.4850 | 2500 | 0.3910 | 0.3824 | 0.6934 | 0.6882 | 0.7156 | 0.3 | 0.3333 | 0.0 | 0.8731 | 0.8 | 0.3704 | 0.0 |
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+ | 0.0438 | 7.7844 | 2600 | 0.3702 | 0.4755 | 0.7359 | 0.7155 | 0.7451 | 0.4615 | 0.4444 | 0.0 | 0.8731 | 0.7778 | 0.4082 | 0.3636 |
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+ | 0.0402 | 8.0838 | 2700 | 0.4042 | 0.4384 | 0.7147 | 0.7078 | 0.7362 | 0.3158 | 0.3333 | 0.0 | 0.8788 | 0.8 | 0.3774 | 0.3636 |
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+ | 0.0264 | 8.3832 | 2800 | 0.4175 | 0.4423 | 0.7080 | 0.6986 | 0.7312 | 0.3 | 0.3636 | 0.0 | 0.8796 | 0.75 | 0.3415 | 0.4615 |
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+ | 0.042 | 8.6826 | 2900 | 0.3898 | 0.4036 | 0.7152 | 0.6863 | 0.7331 | 0.3333 | 0.2222 | 0.0 | 0.8832 | 0.7451 | 0.3077 | 0.3333 |
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+ | 0.0342 | 8.9820 | 3000 | 0.4055 | 0.4390 | 0.7209 | 0.7063 | 0.7448 | 0.3333 | 0.3636 | 0.0 | 0.8788 | 0.7636 | 0.4 | 0.3333 |
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+ | 0.0268 | 9.2814 | 3100 | 0.4006 | 0.4312 | 0.7147 | 0.6957 | 0.7362 | 0.3529 | 0.3333 | 0.0 | 0.8808 | 0.7692 | 0.3182 | 0.3636 |
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+ | 0.0253 | 9.5808 | 3200 | 0.4121 | 0.4302 | 0.7062 | 0.6983 | 0.7302 | 0.3636 | 0.2667 | 0.0 | 0.8705 | 0.7917 | 0.3556 | 0.3636 |
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+ | 0.0179 | 9.8802 | 3300 | 0.4356 | 0.3574 | 0.6967 | 0.6606 | 0.7206 | 0.4 | 0.25 | 0.0 | 0.8788 | 0.7407 | 0.2326 | 0.0 |
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+ | 0.018 | 10.1796 | 3400 | 0.4594 | 0.4081 | 0.7066 | 0.6713 | 0.7299 | 0.4706 | 0.3636 | 0.0 | 0.8821 | 0.7241 | 0.2162 | 0.2 |
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+ | 0.0151 | 10.4790 | 3500 | 0.4579 | 0.3911 | 0.7190 | 0.6807 | 0.7422 | 0.375 | 0.2222 | 0.0 | 0.8844 | 0.7636 | 0.2703 | 0.2222 |
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+ | 0.0124 | 10.7784 | 3600 | 0.4415 | 0.3710 | 0.6988 | 0.6648 | 0.7286 | 0.2857 | 0.2222 | 0.0 | 0.8744 | 0.7547 | 0.2381 | 0.2222 |
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+ | 0.0193 | 11.0778 | 3700 | 0.4514 | 0.3797 | 0.6903 | 0.6708 | 0.7172 | 0.3529 | 0.2 | 0.0 | 0.8763 | 0.7018 | 0.3043 | 0.2222 |
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+ | 0.0138 | 11.3772 | 3800 | 0.4427 | 0.3681 | 0.6909 | 0.6637 | 0.7065 | 0.25 | 0.25 | 0.0 | 0.8705 | 0.7273 | 0.2791 | 0.2 |
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+ | 0.0101 | 11.6766 | 3900 | 0.4641 | 0.4035 | 0.6964 | 0.6718 | 0.7203 | 0.3478 | 0.4 | 0.0 | 0.8705 | 0.75 | 0.2564 | 0.2 |
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+ | 0.0112 | 11.9760 | 4000 | 0.4713 | 0.4260 | 0.7048 | 0.6820 | 0.7260 | 0.3158 | 0.4 | 0.0 | 0.8731 | 0.7917 | 0.2381 | 0.3636 |
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+ | 0.0118 | 12.2754 | 4100 | 0.4722 | 0.3811 | 0.6941 | 0.6751 | 0.7148 | 0.2857 | 0.25 | 0.0 | 0.8731 | 0.7547 | 0.3043 | 0.2 |
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+ | 0.0086 | 12.5749 | 4200 | 0.4911 | 0.4104 | 0.7009 | 0.6925 | 0.7216 | 0.3077 | 0.3636 | 0.0 | 0.8776 | 0.7636 | 0.36 | 0.2 |
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+ | 0.0099 | 12.8743 | 4300 | 0.4928 | 0.3666 | 0.6786 | 0.6584 | 0.7076 | 0.2857 | 0.25 | 0.0 | 0.8796 | 0.7018 | 0.2273 | 0.2222 |
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+ | 0.0074 | 13.1737 | 4400 | 0.4873 | 0.3970 | 0.7072 | 0.6954 | 0.7234 | 0.3158 | 0.2222 | 0.0 | 0.8776 | 0.7636 | 0.4 | 0.2 |
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+ | 0.0066 | 13.4731 | 4500 | 0.4947 | 0.4096 | 0.7080 | 0.6896 | 0.7286 | 0.3158 | 0.3636 | 0.0 | 0.8832 | 0.7843 | 0.2979 | 0.2222 |
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+ | 0.0071 | 13.7725 | 4600 | 0.4939 | 0.3922 | 0.7055 | 0.6848 | 0.7302 | 0.3529 | 0.2222 | 0.0 | 0.8832 | 0.7241 | 0.3404 | 0.2222 |
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+ | 0.0083 | 14.0719 | 4700 | 0.5015 | 0.3803 | 0.6997 | 0.6775 | 0.7255 | 0.3 | 0.2222 | 0.0 | 0.8832 | 0.7368 | 0.2979 | 0.2222 |
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+ | 0.0065 | 14.3713 | 4800 | 0.5024 | 0.4186 | 0.7038 | 0.6867 | 0.7255 | 0.3636 | 0.4 | 0.0 | 0.8763 | 0.7636 | 0.3043 | 0.2222 |
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+ | 0.0055 | 14.6707 | 4900 | 0.5100 | 0.4132 | 0.7035 | 0.6862 | 0.7292 | 0.3478 | 0.4 | 0.0 | 0.8788 | 0.7547 | 0.3111 | 0.2 |
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+ | 0.0056 | 14.9701 | 5000 | 0.5013 | 0.4411 | 0.7059 | 0.6961 | 0.7357 | 0.2727 | 0.4 | 0.0 | 0.8808 | 0.7547 | 0.3182 | 0.4615 |
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+ | 0.0044 | 15.2695 | 5100 | 0.5120 | 0.3840 | 0.6977 | 0.6843 | 0.7201 | 0.2857 | 0.2222 | 0.0 | 0.8776 | 0.7273 | 0.375 | 0.2 |
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+ | 0.0052 | 15.5689 | 5200 | 0.5334 | 0.3811 | 0.7035 | 0.6818 | 0.7294 | 0.3 | 0.2 | 0.0 | 0.8844 | 0.75 | 0.3111 | 0.2222 |
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+ | 0.0041 | 15.8683 | 5300 | 0.5184 | 0.4135 | 0.7143 | 0.6895 | 0.7352 | 0.3158 | 0.4 | 0.0 | 0.8832 | 0.7547 | 0.3182 | 0.2222 |
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+ | 0.0052 | 16.1677 | 5400 | 0.5182 | 0.4188 | 0.7186 | 0.6910 | 0.7352 | 0.3529 | 0.4 | 0.0 | 0.8832 | 0.7547 | 0.3182 | 0.2222 |
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+ | 0.0036 | 16.4671 | 5500 | 0.5208 | 0.4125 | 0.7164 | 0.6949 | 0.7370 | 0.3 | 0.3636 | 0.0 | 0.8832 | 0.8 | 0.3182 | 0.2222 |
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+ | 0.004 | 16.7665 | 5600 | 0.5382 | 0.4086 | 0.7059 | 0.6842 | 0.7315 | 0.3 | 0.4 | 0.0 | 0.8788 | 0.7407 | 0.3182 | 0.2222 |
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+ | 0.0037 | 17.0659 | 5700 | 0.5258 | 0.4208 | 0.7118 | 0.6959 | 0.7299 | 0.3158 | 0.4 | 0.0 | 0.8776 | 0.7547 | 0.375 | 0.2222 |
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+ | 0.0036 | 17.3653 | 5800 | 0.5283 | 0.4065 | 0.7101 | 0.6873 | 0.7326 | 0.3158 | 0.3636 | 0.0 | 0.8788 | 0.7692 | 0.3182 | 0.2 |
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+ | 0.0031 | 17.6647 | 5900 | 0.5315 | 0.4107 | 0.7041 | 0.6840 | 0.7247 | 0.3158 | 0.4 | 0.0 | 0.8776 | 0.7547 | 0.3043 | 0.2222 |
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+ | 0.0041 | 17.9641 | 6000 | 0.5419 | 0.4084 | 0.6977 | 0.6806 | 0.7232 | 0.3636 | 0.3636 | 0.0 | 0.8776 | 0.7273 | 0.3043 | 0.2222 |
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+ | 0.0031 | 18.2635 | 6100 | 0.5469 | 0.4071 | 0.7 | 0.6784 | 0.7253 | 0.3158 | 0.4 | 0.0 | 0.8731 | 0.7273 | 0.3111 | 0.2222 |
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+ | 0.003 | 18.5629 | 6200 | 0.5477 | 0.4213 | 0.7080 | 0.6877 | 0.7292 | 0.4 | 0.4 | 0.0 | 0.8821 | 0.7407 | 0.3043 | 0.2222 |
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+ | 0.0032 | 18.8623 | 6300 | 0.5395 | 0.4054 | 0.7003 | 0.6842 | 0.7208 | 0.3158 | 0.4 | 0.0 | 0.8808 | 0.7547 | 0.3043 | 0.1818 |
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+ | 0.0033 | 19.1617 | 6400 | 0.5444 | 0.3989 | 0.7038 | 0.6968 | 0.7240 | 0.3478 | 0.2222 | 0.0 | 0.8808 | 0.7843 | 0.375 | 0.1818 |
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+ | 0.0032 | 19.4611 | 6500 | 0.5482 | 0.4047 | 0.6982 | 0.6817 | 0.7182 | 0.3158 | 0.4 | 0.0 | 0.8763 | 0.7547 | 0.3043 | 0.1818 |
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+ | 0.0025 | 19.7605 | 6600 | 0.5498 | 0.4047 | 0.7003 | 0.6818 | 0.7221 | 0.3158 | 0.4 | 0.0 | 0.8763 | 0.7407 | 0.3182 | 0.1818 |
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+ | 0.0027 | 20.0599 | 6700 | 0.5542 | 0.4134 | 0.6997 | 0.6879 | 0.7232 | 0.3636 | 0.4 | 0.0 | 0.8808 | 0.7273 | 0.3404 | 0.1818 |
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+ | 0.003 | 20.3593 | 6800 | 0.5599 | 0.3788 | 0.6962 | 0.6762 | 0.7214 | 0.3158 | 0.2222 | 0.0 | 0.8821 | 0.7273 | 0.3043 | 0.2 |
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+ | 0.0025 | 20.6587 | 6900 | 0.5556 | 0.4121 | 0.7041 | 0.6838 | 0.7247 | 0.3158 | 0.4 | 0.0 | 0.8731 | 0.7692 | 0.3043 | 0.2222 |
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+ | 0.0027 | 20.9581 | 7000 | 0.5579 | 0.4010 | 0.6959 | 0.6781 | 0.7214 | 0.3158 | 0.4 | 0.0 | 0.8776 | 0.7273 | 0.3043 | 0.1818 |
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+ | 0.0025 | 21.2575 | 7100 | 0.5583 | 0.3762 | 0.6941 | 0.6754 | 0.7188 | 0.3158 | 0.2222 | 0.0 | 0.8821 | 0.7273 | 0.3043 | 0.1818 |
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+ | 0.0025 | 21.5569 | 7200 | 0.5586 | 0.4021 | 0.6941 | 0.6771 | 0.7169 | 0.3158 | 0.4 | 0.0 | 0.8718 | 0.7407 | 0.3043 | 0.1818 |
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+ | 0.0025 | 21.8563 | 7300 | 0.5612 | 0.3767 | 0.6923 | 0.6721 | 0.7188 | 0.3158 | 0.2222 | 0.0 | 0.8718 | 0.7273 | 0.3182 | 0.1818 |
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+ | 0.0025 | 22.1557 | 7400 | 0.5688 | 0.3807 | 0.6962 | 0.6744 | 0.7214 | 0.3333 | 0.2222 | 0.0 | 0.8776 | 0.7273 | 0.3043 | 0.2 |
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+ | 0.0025 | 22.4551 | 7500 | 0.5707 | 0.4054 | 0.6979 | 0.6771 | 0.7227 | 0.3333 | 0.4 | 0.0 | 0.8731 | 0.7273 | 0.3043 | 0.2 |
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+ | 0.0024 | 22.7545 | 7600 | 0.5702 | 0.4055 | 0.7 | 0.6809 | 0.7247 | 0.3158 | 0.4 | 0.0 | 0.8776 | 0.7407 | 0.3043 | 0.2 |
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+ | 0.0022 | 23.0539 | 7700 | 0.5706 | 0.4119 | 0.7038 | 0.6858 | 0.7266 | 0.3158 | 0.4 | 0.0 | 0.8776 | 0.7273 | 0.3404 | 0.2222 |
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+ | 0.0017 | 23.3533 | 7800 | 0.5725 | 0.4067 | 0.7 | 0.6797 | 0.7240 | 0.3158 | 0.4 | 0.0 | 0.8776 | 0.7273 | 0.3043 | 0.2222 |
139
+ | 0.0026 | 23.6527 | 7900 | 0.5774 | 0.4061 | 0.6979 | 0.6773 | 0.7227 | 0.3158 | 0.4 | 0.0 | 0.8731 | 0.7273 | 0.3043 | 0.2222 |
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+ | 0.0023 | 23.9521 | 8000 | 0.5758 | 0.4087 | 0.7021 | 0.6818 | 0.7253 | 0.3158 | 0.4 | 0.0 | 0.8776 | 0.7407 | 0.3043 | 0.2222 |
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+ | 0.0022 | 24.2515 | 8100 | 0.5774 | 0.4067 | 0.7 | 0.6797 | 0.7240 | 0.3158 | 0.4 | 0.0 | 0.8776 | 0.7273 | 0.3043 | 0.2222 |
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+ | 0.0022 | 24.5509 | 8200 | 0.5764 | 0.4067 | 0.7 | 0.6797 | 0.7240 | 0.3158 | 0.4 | 0.0 | 0.8776 | 0.7273 | 0.3043 | 0.2222 |
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+ | 0.0023 | 24.8503 | 8300 | 0.5770 | 0.4036 | 0.6979 | 0.6788 | 0.7240 | 0.3158 | 0.4 | 0.0 | 0.8776 | 0.7273 | 0.3043 | 0.2 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.47.1
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+ - Pytorch 2.5.1+cu121
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
config.json ADDED
@@ -0,0 +1,41 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "_name_or_path": "w11wo/sundanese-roberta-base-emotion-classifier",
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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": "sadness",
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+ "1": "joy",
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+ "2": "fear",
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