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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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- accuracy
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- f1
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model-index:
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- name: distilbert-base-uncased-finetuned-intro-verizon2
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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-finetuned-intro-verizon2
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0327
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- Accuracy: 1.0
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- F1: 1.0
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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: 64
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- eval_batch_size: 64
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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 | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| 1.3459 | 1.0 | 7 | 1.2548 | 0.5814 | 0.4575 |
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| 1.1898 | 2.0 | 14 | 1.0488 | 0.7209 | 0.6261 |
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| 1.1052 | 3.0 | 21 | 0.7911 | 0.7442 | 0.6506 |
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| 0.7628 | 4.0 | 28 | 0.5534 | 1.0 | 1.0 |
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| 0.6325 | 5.0 | 35 | 0.3608 | 1.0 | 1.0 |
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| 0.303 | 6.0 | 42 | 0.2387 | 1.0 | 1.0 |
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| 0.2297 | 7.0 | 49 | 0.1626 | 1.0 | 1.0 |
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| 0.1663 | 8.0 | 56 | 0.1152 | 1.0 | 1.0 |
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| 0.1232 | 9.0 | 63 | 0.0866 | 1.0 | 1.0 |
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| 0.1056 | 10.0 | 70 | 0.0683 | 1.0 | 1.0 |
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| 0.0802 | 11.0 | 77 | 0.0572 | 1.0 | 1.0 |
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| 0.0589 | 12.0 | 84 | 0.0497 | 1.0 | 1.0 |
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| 0.0561 | 13.0 | 91 | 0.0445 | 1.0 | 1.0 |
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| 0.0567 | 14.0 | 98 | 0.0404 | 1.0 | 1.0 |
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| 0.0457 | 15.0 | 105 | 0.0376 | 1.0 | 1.0 |
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| 0.0417 | 16.0 | 112 | 0.0357 | 1.0 | 1.0 |
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| 0.0412 | 17.0 | 119 | 0.0344 | 1.0 | 1.0 |
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| 0.0389 | 18.0 | 126 | 0.0335 | 1.0 | 1.0 |
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| 0.04 | 19.0 | 133 | 0.0329 | 1.0 | 1.0 |
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| 0.0394 | 20.0 | 140 | 0.0327 | 1.0 | 1.0 |
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### Framework versions
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- Transformers 4.16.2
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- Pytorch 2.1.0+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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