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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: google-bert/bert-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: test_trainer
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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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# test_trainer
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This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9995
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- Accuracy: 0.581
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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: 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: 3.0
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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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| No log | 1.0 | 125 | 1.3630 | 0.414 |
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| No log | 2.0 | 250 | 1.0149 | 0.55 |
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| No log | 3.0 | 375 | 0.9995 | 0.581 |
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### Framework versions
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- Transformers 4.46.0
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- Pytorch 2.5.0+cu124
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- Datasets 3.0.2
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- Tokenizers 0.20.1
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