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Yuvrajg2107
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roberta-base-cpp

Text Classification
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roberta
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  1. README.md +26 -14
  2. model.safetensors +1 -1
README.md CHANGED
@@ -18,8 +18,8 @@ should probably proofread and complete it, then remove this comment. -->
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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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  ### 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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  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: 0.0844
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+ - Accuracy: 0.9550
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  ## Model description
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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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+ | 0.1085 | 0.05 | 1000 | 0.1080 | 0.9183 |
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+ | 0.0716 | 0.1 | 2000 | 0.2524 | 0.8473 |
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+ | 0.0615 | 0.15 | 3000 | 0.1182 | 0.9299 |
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+ | 0.0648 | 0.2 | 4000 | 0.0757 | 0.9498 |
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+ | 0.0522 | 0.25 | 5000 | 0.1201 | 0.9273 |
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+ | 0.0377 | 0.3 | 6000 | 0.0846 | 0.9555 |
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+ | 0.0447 | 0.35 | 7000 | 0.1036 | 0.9323 |
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+ | 0.0421 | 0.4 | 8000 | 0.1804 | 0.8914 |
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+ | 0.0364 | 0.45 | 9000 | 0.0494 | 0.9628 |
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+ | 0.0301 | 0.5 | 10000 | 0.0583 | 0.9689 |
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+ | 0.0281 | 0.55 | 11000 | 0.0554 | 0.9689 |
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+ | 0.0362 | 0.6 | 12000 | 0.0898 | 0.9428 |
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+ | 0.022 | 0.65 | 13000 | 0.0772 | 0.9687 |
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+ | 0.0221 | 0.7 | 14000 | 0.0706 | 0.9613 |
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+ | 0.0256 | 0.75 | 15000 | 0.0487 | 0.9719 |
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+ | 0.0215 | 0.8 | 16000 | 0.0427 | 0.9765 |
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+ | 0.0162 | 0.85 | 17000 | 0.0437 | 0.9742 |
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+ | 0.0186 | 0.9 | 18000 | 0.0613 | 0.9680 |
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+ | 0.0211 | 0.95 | 19000 | 0.0950 | 0.9514 |
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+ | 0.0136 | 1.0 | 20000 | 0.0844 | 0.9550 |
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  ### Framework versions
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+ - Transformers 4.57.3
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  - Pytorch 2.8.0+cu126
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+ - Datasets 4.4.2
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  - Tokenizers 0.22.1
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