Model save
Browse files- README.md +85 -0
- generation_config.json +6 -0
README.md
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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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- precision
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- recall
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- f1
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model-index:
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- name: sentiment-base-1
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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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# sentiment-base-1
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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: 0.7891
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- Accuracy: 0.8972
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- Precision: 0.8796
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- Recall: 0.8698
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- F1: 0.8745
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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: 5e-05
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- train_batch_size: 30
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- eval_batch_size: 8
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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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- num_epochs: 20.0
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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| 0.411 | 1.0 | 122 | 0.2751 | 0.8722 | 0.8474 | 0.8421 | 0.8446 |
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| 0.2264 | 2.0 | 244 | 0.3037 | 0.8872 | 0.8574 | 0.8977 | 0.8719 |
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| 0.1467 | 3.0 | 366 | 0.3442 | 0.8772 | 0.8465 | 0.8756 | 0.8582 |
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| 0.0961 | 4.0 | 488 | 0.3737 | 0.8997 | 0.8819 | 0.8741 | 0.8778 |
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| 0.0726 | 5.0 | 610 | 0.4306 | 0.8997 | 0.8835 | 0.8716 | 0.8772 |
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| 0.0514 | 6.0 | 732 | 0.6449 | 0.8847 | 0.8546 | 0.8884 | 0.8677 |
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| 0.0532 | 7.0 | 854 | 0.5595 | 0.8972 | 0.8754 | 0.8773 | 0.8764 |
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| 0.0274 | 8.0 | 976 | 0.6728 | 0.8872 | 0.8687 | 0.8552 | 0.8615 |
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| 0.0186 | 9.0 | 1098 | 0.6218 | 0.9073 | 0.8977 | 0.8744 | 0.8849 |
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| 0.0121 | 10.0 | 1220 | 0.6576 | 0.8922 | 0.8766 | 0.8587 | 0.8669 |
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| 0.0244 | 11.0 | 1342 | 0.7507 | 0.8972 | 0.8940 | 0.8523 | 0.8695 |
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| 0.0062 | 12.0 | 1464 | 0.6859 | 0.8972 | 0.8849 | 0.8623 | 0.8724 |
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| 0.0099 | 13.0 | 1586 | 0.6514 | 0.9073 | 0.8904 | 0.8844 | 0.8873 |
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| 0.0087 | 14.0 | 1708 | 0.7604 | 0.8997 | 0.8852 | 0.8691 | 0.8765 |
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| 0.0056 | 15.0 | 1830 | 0.7282 | 0.9023 | 0.8875 | 0.8733 | 0.8799 |
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| 0.0063 | 16.0 | 1952 | 0.6987 | 0.9123 | 0.8965 | 0.8904 | 0.8934 |
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| 0.0071 | 17.0 | 2074 | 0.7402 | 0.9048 | 0.8897 | 0.8776 | 0.8833 |
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| 0.0023 | 18.0 | 2196 | 0.7846 | 0.8922 | 0.8719 | 0.8662 | 0.8690 |
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| 0.0043 | 19.0 | 2318 | 0.7948 | 0.8922 | 0.8719 | 0.8662 | 0.8690 |
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| 0.0021 | 20.0 | 2440 | 0.7891 | 0.8972 | 0.8796 | 0.8698 | 0.8745 |
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### Framework versions
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- Transformers 4.39.3
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- Pytorch 2.3.0+cu121
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- Datasets 2.19.1
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- Tokenizers 0.15.2
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 0,
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"pad_token_id": 0,
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"transformers_version": "4.39.3"
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}
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