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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: 0.6883 |
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- F1: 0.8201 |
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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: 3 |
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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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| 2.1343 | 0.11 | 2000 | 1.7374 | 0.2664 | |
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| 1.2506 | 0.22 | 4000 | 1.1294 | 0.5441 | |
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| 0.9268 | 0.33 | 6000 | 0.8991 | 0.6547 | |
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| 0.7993 | 0.44 | 8000 | 0.8401 | 0.6819 | |
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| 0.6985 | 0.54 | 10000 | 0.7629 | 0.7245 | |
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| 0.6418 | 0.65 | 12000 | 0.7507 | 0.7559 | |
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| 0.5887 | 0.76 | 14000 | 0.6858 | 0.7796 | |
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| 0.5462 | 0.87 | 16000 | 0.6852 | 0.7872 | |
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| 0.508 | 0.98 | 18000 | 0.6731 | 0.7836 | |
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| 0.4222 | 1.09 | 20000 | 0.6884 | 0.7902 | |
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| 0.3948 | 1.2 | 22000 | 0.6809 | 0.7897 | |
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| 0.3947 | 1.31 | 24000 | 0.6894 | 0.7935 | |
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| 0.3779 | 1.42 | 26000 | 0.6702 | 0.8026 | |
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| 0.3488 | 1.53 | 28000 | 0.6762 | 0.7935 | |
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| 0.3461 | 1.63 | 30000 | 0.6737 | 0.8054 | |
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| 0.3372 | 1.74 | 32000 | 0.6720 | 0.8062 | |
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| 0.3275 | 1.85 | 34000 | 0.6526 | 0.8156 | |
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| 0.3224 | 1.96 | 36000 | 0.6717 | 0.8068 | |
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| 0.2425 | 2.07 | 38000 | 0.6810 | 0.8143 | |
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| 0.2423 | 2.18 | 40000 | 0.6668 | 0.8196 | |
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| 0.2394 | 2.29 | 42000 | 0.7014 | 0.8125 | |
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| 0.2247 | 2.4 | 44000 | 0.6842 | 0.8167 | |
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| 0.2253 | 2.51 | 46000 | 0.7012 | 0.8130 | |
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| 0.2225 | 2.62 | 48000 | 0.6907 | 0.8178 | |
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| 0.2074 | 2.72 | 50000 | 0.6814 | 0.8206 | |
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| 0.2095 | 2.83 | 52000 | 0.6928 | 0.8192 | |
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| 0.2018 | 2.94 | 54000 | 0.6883 | 0.8201 | |
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### Framework versions |
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- Transformers 4.34.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.0 |
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