Copying README.md from Yuvrajg2107/roberta-base-cpp
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---
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library_name: transformers
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license: mit
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base_model: FacebookAI/roberta-base
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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: roberta-base-cpp
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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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# roberta-base-cpp
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This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1043
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- Accuracy: 0.9419
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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: 2
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 4
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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: 1
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- mixed_precision_training: Native AMP
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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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| 0.1244 | 0.125 | 1000 | 0.0842 | 0.931 |
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| 0.0851 | 0.25 | 2000 | 0.2041 | 0.7715 |
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| 0.0632 | 0.375 | 3000 | 0.1610 | 0.9123 |
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| 0.0521 | 0.5 | 4000 | 0.0907 | 0.9224 |
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| 0.0426 | 0.625 | 5000 | 0.2447 | 0.8784 |
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| 0.0341 | 0.75 | 6000 | 0.0667 | 0.9641 |
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| 0.0252 | 0.875 | 7000 | 0.0872 | 0.957 |
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| 0.0184 | 1.0 | 8000 | 0.1043 | 0.9419 |
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### Framework versions
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- Transformers 4.57.1
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- Pytorch 2.8.0+cu126
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- Datasets 4.4.1
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- Tokenizers 0.22.1
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