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--- |
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license: mit |
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base_model: indolem/indobert-base-uncased |
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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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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: indobert-base-uncased-reddit-indonesia-sarcastic |
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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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# indobert-base-uncased-reddit-indonesia-sarcastic |
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This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5000 |
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- Accuracy: 0.7670 |
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- F1: 0.5671 |
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- Precision: 0.5295 |
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- Recall: 0.6105 |
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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: 1e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 64 |
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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: cosine |
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- num_epochs: 100.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.5121 | 1.0 | 309 | 0.4942 | 0.7378 | 0.4774 | 0.4761 | 0.4788 | |
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| 0.4513 | 2.0 | 618 | 0.4422 | 0.7952 | 0.4956 | 0.6455 | 0.4023 | |
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| 0.4078 | 3.0 | 927 | 0.4771 | 0.7980 | 0.4075 | 0.7656 | 0.2776 | |
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| 0.3686 | 4.0 | 1236 | 0.4755 | 0.8051 | 0.4898 | 0.7097 | 0.3739 | |
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| 0.3358 | 5.0 | 1545 | 0.4864 | 0.7753 | 0.5768 | 0.5455 | 0.6119 | |
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| 0.299 | 6.0 | 1854 | 0.5038 | 0.7633 | 0.5729 | 0.5221 | 0.6346 | |
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| 0.2602 | 7.0 | 2163 | 0.5242 | 0.7888 | 0.5387 | 0.5939 | 0.4929 | |
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| 0.2184 | 8.0 | 2472 | 0.6153 | 0.7817 | 0.5523 | 0.5672 | 0.5382 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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