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--- |
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base_model: xxxxxxxxx |
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tags: |
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- generated_from_trainer |
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datasets: |
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- AmazonScience/massive |
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metrics: |
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- f1 |
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model-index: |
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- name: massive_indo |
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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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# massive_indo |
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This model is a fine-tuned version of [xxxxxxxxx](https://huggingface.co/xxxxxxxxx) on the massive dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6572 |
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- F1: 0.9265 |
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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: 32 |
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- eval_batch_size: 32 |
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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 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 4.6759 | 0.7 | 100 | 4.5686 | 0.0756 | |
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| 4.1696 | 1.41 | 200 | 4.1337 | 0.1459 | |
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| 3.7162 | 2.11 | 300 | 3.7519 | 0.2513 | |
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| 3.3933 | 2.82 | 400 | 3.4123 | 0.3291 | |
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| 3.0368 | 3.52 | 500 | 3.0874 | 0.4287 | |
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| 2.7163 | 4.23 | 600 | 2.7851 | 0.5446 | |
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| 2.4295 | 4.93 | 700 | 2.5342 | 0.5967 | |
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| 2.192 | 5.63 | 800 | 2.2814 | 0.6738 | |
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| 1.9818 | 6.34 | 900 | 2.0643 | 0.7221 | |
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| 1.7487 | 7.04 | 1000 | 1.8860 | 0.7589 | |
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| 1.6227 | 7.75 | 1100 | 1.7132 | 0.8021 | |
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| 1.4186 | 8.45 | 1200 | 1.5550 | 0.8249 | |
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| 1.2316 | 9.15 | 1300 | 1.4266 | 0.8378 | |
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| 1.1508 | 9.86 | 1400 | 1.3024 | 0.8547 | |
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| 1.0137 | 10.56 | 1500 | 1.1962 | 0.8708 | |
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| 0.9242 | 11.27 | 1600 | 1.1050 | 0.8807 | |
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| 0.877 | 11.97 | 1700 | 1.0273 | 0.8908 | |
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| 0.7244 | 12.68 | 1800 | 0.9580 | 0.8946 | |
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| 0.7141 | 13.38 | 1900 | 0.8928 | 0.9016 | |
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| 0.6071 | 14.08 | 2000 | 0.8448 | 0.9128 | |
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| 0.6166 | 14.79 | 2100 | 0.7980 | 0.9112 | |
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| 0.6017 | 15.49 | 2200 | 0.7613 | 0.9175 | |
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| 0.5192 | 16.2 | 2300 | 0.7300 | 0.9204 | |
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| 0.4669 | 16.9 | 2400 | 0.7112 | 0.9172 | |
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| 0.4539 | 17.61 | 2500 | 0.6872 | 0.9247 | |
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| 0.438 | 18.31 | 2600 | 0.6698 | 0.9248 | |
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| 0.4435 | 19.01 | 2700 | 0.6612 | 0.9256 | |
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| 0.4141 | 19.72 | 2800 | 0.6572 | 0.9265 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.0.1+cu118 |
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- Tokenizers 0.13.3 |
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