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MHGanainy
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roberta-base-downstream-build_rr

Token Classification
Transformers
Safetensors
roberta
Generated from Trainer
Inference Endpoints
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  1. README.md +21 -24
  2. model.safetensors +1 -1
README.md CHANGED
@@ -18,14 +18,14 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8272
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- - Precision-macro: 0.6089
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- - Recall-macro: 0.5868
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- - Macro-f1: 0.5926
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- - Precision-micro: 0.7798
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- - Recall-micro: 0.7798
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- - Micro-f1: 0.7798
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- - Accuracy: 0.7798
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  ## Model description
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@@ -45,8 +45,8 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 3e-05
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- - train_batch_size: 4
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- - eval_batch_size: 4
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  - seed: 1
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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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  | Training Loss | Epoch | Step | Validation Loss | Precision-macro | Recall-macro | Macro-f1 | Precision-micro | Recall-micro | Micro-f1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:--------:|:--------:|
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- | No log | 1.0 | 62 | 1.1797 | 0.3651 | 0.2425 | 0.2406 | 0.6509 | 0.6509 | 0.6509 | 0.6509 |
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- | No log | 2.0 | 124 | 0.8354 | 0.5350 | 0.5291 | 0.5255 | 0.7350 | 0.7350 | 0.7350 | 0.7350 |
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- | No log | 3.0 | 186 | 0.8058 | 0.5559 | 0.5382 | 0.5366 | 0.7343 | 0.7343 | 0.7343 | 0.7343 |
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- | No log | 4.0 | 248 | 0.7718 | 0.6246 | 0.5201 | 0.5300 | 0.7503 | 0.7503 | 0.7503 | 0.7503 |
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- | No log | 5.0 | 310 | 0.7307 | 0.5890 | 0.5463 | 0.5579 | 0.7642 | 0.7642 | 0.7642 | 0.7642 |
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- | No log | 6.0 | 372 | 0.7099 | 0.6076 | 0.5431 | 0.5481 | 0.7746 | 0.7746 | 0.7746 | 0.7746 |
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- | No log | 7.0 | 434 | 0.7072 | 0.6090 | 0.5126 | 0.5261 | 0.7812 | 0.7812 | 0.7812 | 0.7812 |
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- | No log | 8.0 | 496 | 0.6919 | 0.6321 | 0.5471 | 0.5676 | 0.7826 | 0.7826 | 0.7826 | 0.7826 |
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- | 0.8758 | 9.0 | 558 | 0.7503 | 0.5666 | 0.5818 | 0.5696 | 0.7735 | 0.7735 | 0.7735 | 0.7735 |
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- | 0.8758 | 10.0 | 620 | 0.7512 | 0.6054 | 0.5656 | 0.5755 | 0.7784 | 0.7784 | 0.7784 | 0.7784 |
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- | 0.8758 | 11.0 | 682 | 0.7656 | 0.6086 | 0.5835 | 0.5913 | 0.7829 | 0.7829 | 0.7829 | 0.7829 |
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- | 0.8758 | 12.0 | 744 | 0.7861 | 0.5972 | 0.5885 | 0.5843 | 0.7739 | 0.7739 | 0.7739 | 0.7739 |
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- | 0.8758 | 13.0 | 806 | 0.8239 | 0.5975 | 0.5749 | 0.5701 | 0.7780 | 0.7780 | 0.7780 | 0.7780 |
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- | 0.8758 | 14.0 | 868 | 0.8272 | 0.6089 | 0.5868 | 0.5926 | 0.7798 | 0.7798 | 0.7798 | 0.7798 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8610
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+ - Precision-macro: 0.6015
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+ - Recall-macro: 0.5642
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+ - Macro-f1: 0.5742
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+ - Precision-micro: 0.7871
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+ - Recall-micro: 0.7871
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+ - Micro-f1: 0.7871
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+ - Accuracy: 0.7871
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 3e-05
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+ - train_batch_size: 2
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+ - eval_batch_size: 2
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  - seed: 1
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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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  | Training Loss | Epoch | Step | Validation Loss | Precision-macro | Recall-macro | Macro-f1 | Precision-micro | Recall-micro | Micro-f1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:--------:|:--------:|
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+ | No log | 1.0 | 124 | 0.9703 | 0.5485 | 0.3447 | 0.3566 | 0.7155 | 0.7155 | 0.7155 | 0.7155 |
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+ | No log | 2.0 | 248 | 0.8005 | 0.5181 | 0.5222 | 0.5080 | 0.7353 | 0.7353 | 0.7353 | 0.7353 |
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+ | No log | 3.0 | 372 | 0.8156 | 0.5626 | 0.5322 | 0.5288 | 0.7454 | 0.7454 | 0.7454 | 0.7454 |
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+ | No log | 4.0 | 496 | 0.7056 | 0.5881 | 0.5197 | 0.5180 | 0.7704 | 0.7704 | 0.7704 | 0.7704 |
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+ | 1.0549 | 5.0 | 620 | 0.7526 | 0.5878 | 0.5906 | 0.5775 | 0.7642 | 0.7642 | 0.7642 | 0.7642 |
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+ | 1.0549 | 6.0 | 744 | 0.7094 | 0.6336 | 0.5395 | 0.5649 | 0.7812 | 0.7812 | 0.7812 | 0.7812 |
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+ | 1.0549 | 7.0 | 868 | 0.7391 | 0.6475 | 0.5339 | 0.5535 | 0.7808 | 0.7808 | 0.7808 | 0.7808 |
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+ | 1.0549 | 8.0 | 992 | 0.7354 | 0.6169 | 0.5756 | 0.5881 | 0.7930 | 0.7930 | 0.7930 | 0.7930 |
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+ | 0.545 | 9.0 | 1116 | 0.8143 | 0.5951 | 0.5963 | 0.5928 | 0.7805 | 0.7805 | 0.7805 | 0.7805 |
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+ | 0.545 | 10.0 | 1240 | 0.8352 | 0.6029 | 0.5915 | 0.5918 | 0.7794 | 0.7794 | 0.7794 | 0.7794 |
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+ | 0.545 | 11.0 | 1364 | 0.8610 | 0.6015 | 0.5642 | 0.5742 | 0.7871 | 0.7871 | 0.7871 | 0.7871 |
 
 
 
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  ### Framework versions
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