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---
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library_name: transformers
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license: apache-2.0
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base_model: distilbert/distilbert-base-cased
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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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model-index:
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- name: binary_classifier
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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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# binary_classifier
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This model is a fine-tuned version of [distilbert/distilbert-base-cased](https://huggingface.co/distilbert/distilbert-base-cased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6459
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- Accuracy: 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: 8
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.6437 | 1.0 | 9 | 0.6773 | 0.6667 |
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| 0.65 | 2.0 | 18 | 0.6628 | 1.0 |
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| 0.6561 | 3.0 | 27 | 0.6575 | 1.0 |
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| 0.6398 | 4.0 | 36 | 0.6532 | 1.0 |
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| 0.6594 | 5.0 | 45 | 0.6516 | 1.0 |
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### Framework versions
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- Transformers 4.46.3
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- Pytorch 2.5.1+cpu
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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