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README.md
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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_3_ternary
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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_3_ternary
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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: 1.7987
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- F1: 0.7460
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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 | 289 | 0.5903 | 0.6893 |
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| 0.5417 | 2.0 | 578 | 0.5822 | 0.7130 |
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| 0.5417 | 3.0 | 867 | 0.6471 | 0.7385 |
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| 0.2298 | 4.0 | 1156 | 0.8933 | 0.7322 |
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| 0.2298 | 5.0 | 1445 | 1.1002 | 0.7147 |
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| 0.1012 | 6.0 | 1734 | 1.2041 | 0.7249 |
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| 0.0508 | 7.0 | 2023 | 1.3575 | 0.7195 |
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| 0.0508 | 8.0 | 2312 | 1.3896 | 0.7385 |
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| 0.018 | 9.0 | 2601 | 1.5363 | 0.7238 |
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| 0.018 | 10.0 | 2890 | 1.5336 | 0.7364 |
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| 0.0142 | 11.0 | 3179 | 1.6335 | 0.7308 |
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| 0.0142 | 12.0 | 3468 | 1.6915 | 0.7295 |
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| 0.0047 | 13.0 | 3757 | 1.7087 | 0.7427 |
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| 0.0058 | 14.0 | 4046 | 1.7875 | 0.7378 |
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| 0.0058 | 15.0 | 4335 | 1.7649 | 0.7438 |
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| 0.0051 | 16.0 | 4624 | 1.7987 | 0.7460 |
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| 0.0051 | 17.0 | 4913 | 1.8435 | 0.7404 |
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| 0.0025 | 18.0 | 5202 | 1.9623 | 0.7257 |
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| 0.0025 | 19.0 | 5491 | 1.9005 | 0.7304 |
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| 0.0029 | 20.0 | 5780 | 1.9437 | 0.7374 |
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| 0.0011 | 21.0 | 6069 | 1.9840 | 0.7268 |
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| 0.0011 | 22.0 | 6358 | 1.9411 | 0.7346 |
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| 0.0025 | 23.0 | 6647 | 1.9233 | 0.7438 |
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| 0.0025 | 24.0 | 6936 | 1.9415 | 0.7395 |
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| 0.0015 | 25.0 | 7225 | 1.9481 | 0.7411 |
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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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