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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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model-index: |
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- name: distilbert-base-uncased_fold_2_ternary_v1 |
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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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# distilbert-base-uncased_fold_2_ternary_v1 |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8941 |
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- F1: 0.7889 |
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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: 25 |
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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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| No log | 1.0 | 294 | 0.6025 | 0.7402 | |
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| 0.5688 | 2.0 | 588 | 0.5025 | 0.7943 | |
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| 0.5688 | 3.0 | 882 | 0.6102 | 0.7794 | |
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| 0.2582 | 4.0 | 1176 | 0.8896 | 0.7835 | |
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| 0.2582 | 5.0 | 1470 | 1.0392 | 0.7821 | |
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| 0.1185 | 6.0 | 1764 | 1.0865 | 0.7848 | |
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| 0.0461 | 7.0 | 2058 | 1.2951 | 0.7686 | |
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| 0.0461 | 8.0 | 2352 | 1.3348 | 0.7821 | |
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| 0.0313 | 9.0 | 2646 | 1.4267 | 0.7876 | |
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| 0.0313 | 10.0 | 2940 | 1.4004 | 0.7957 | |
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| 0.0142 | 11.0 | 3234 | 1.5501 | 0.7794 | |
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| 0.0083 | 12.0 | 3528 | 1.5564 | 0.7903 | |
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| 0.0083 | 13.0 | 3822 | 1.5699 | 0.7876 | |
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| 0.0067 | 14.0 | 4116 | 1.7725 | 0.7794 | |
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| 0.0067 | 15.0 | 4410 | 1.7642 | 0.7767 | |
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| 0.0031 | 16.0 | 4704 | 1.7891 | 0.7848 | |
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| 0.0031 | 17.0 | 4998 | 1.8528 | 0.7740 | |
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| 0.0054 | 18.0 | 5292 | 1.8378 | 0.7781 | |
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| 0.003 | 19.0 | 5586 | 1.8223 | 0.7862 | |
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| 0.003 | 20.0 | 5880 | 1.7935 | 0.7930 | |
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| 0.0021 | 21.0 | 6174 | 1.9117 | 0.7808 | |
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| 0.0021 | 22.0 | 6468 | 1.8891 | 0.7930 | |
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| 0.0015 | 23.0 | 6762 | 1.9167 | 0.7916 | |
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| 0.0006 | 24.0 | 7056 | 1.9193 | 0.7862 | |
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| 0.0006 | 25.0 | 7350 | 1.8941 | 0.7889 | |
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### Framework versions |
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- Transformers 4.21.0 |
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- Pytorch 1.12.0+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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