Model save
Browse files- README.md +69 -0
- pytorch_model.bin +1 -1
README.md
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---
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license: mit
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base_model: indobenchmark/indobert-base-p1
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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: indobert-finetuned-aspect-happiness-index
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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-finetuned-aspect-happiness-index
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This model is a fine-tuned version of [indobenchmark/indobert-base-p1](https://huggingface.co/indobenchmark/indobert-base-p1) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1476
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- Accuracy: 0.9732
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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: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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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: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 1.0 | 270 | 0.1291 | 0.9648 |
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| 0.301 | 2.0 | 540 | 0.1708 | 0.9593 |
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| 0.301 | 3.0 | 810 | 0.1350 | 0.9685 |
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| 0.0655 | 4.0 | 1080 | 0.1734 | 0.9648 |
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| 0.0655 | 5.0 | 1350 | 0.1323 | 0.9713 |
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| 0.023 | 6.0 | 1620 | 0.1551 | 0.9676 |
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| 0.023 | 7.0 | 1890 | 0.1558 | 0.9704 |
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| 0.0137 | 8.0 | 2160 | 0.1531 | 0.9732 |
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| 0.0137 | 9.0 | 2430 | 0.1493 | 0.9722 |
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| 0.0056 | 10.0 | 2700 | 0.1476 | 0.9732 |
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### Framework versions
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- Transformers 4.33.1
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.5
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- Tokenizers 0.13.3
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:
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size 497861425
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version https://git-lfs.github.com/spec/v1
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size 497861425
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