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Enyonam
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roberta-base-Roberta-Model

Text Classification
Transformers
PyTorch
roberta
Generated from Trainer
Inference Endpoints
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End of training

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  1. README.md +23 -9
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -17,8 +17,8 @@ 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: 0.7219
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- - F1: 0.6603
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  ## Model description
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@@ -43,22 +43,36 @@ The following hyperparameters were used during training:
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  - seed: 42
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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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- - num_epochs: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 0.8522 | 0.5 | 500 | 0.8126 | 0.6433 |
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- | 0.8087 | 1.0 | 1000 | 0.7935 | 0.6534 |
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- | 0.7826 | 1.5 | 1500 | 0.7585 | 0.6548 |
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- | 0.7753 | 2.01 | 2000 | 0.7447 | 0.6574 |
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- | 0.7473 | 2.51 | 2500 | 0.7219 | 0.6603 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.32.1
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  - Pytorch 2.0.1+cu118
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  - Datasets 2.14.4
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  - Tokenizers 0.13.3
 
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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: 0.7350
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+ - F1: 0.6663
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  ## Model description
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  - seed: 42
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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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+ - num_epochs: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 0.8512 | 0.5 | 500 | 0.7909 | 0.6405 |
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+ | 0.7992 | 1.0 | 1000 | 0.8753 | 0.6407 |
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+ | 0.7667 | 1.5 | 1500 | 0.7786 | 0.6428 |
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+ | 0.7583 | 2.01 | 2000 | 0.7407 | 0.6593 |
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+ | 0.7415 | 2.51 | 2500 | 0.7564 | 0.6555 |
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+ | 0.7337 | 3.01 | 3000 | 0.7536 | 0.6526 |
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+ | 0.7224 | 3.51 | 3500 | 0.7777 | 0.6126 |
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+ | 0.7067 | 4.01 | 4000 | 0.7790 | 0.6552 |
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+ | 0.6693 | 4.51 | 4500 | 0.7497 | 0.6665 |
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+ | 0.6744 | 5.02 | 5000 | 0.7350 | 0.6663 |
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+ | 0.6546 | 5.52 | 5500 | 0.7865 | 0.6714 |
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+ | 0.6725 | 6.02 | 6000 | 0.7639 | 0.6721 |
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+ | 0.6361 | 6.52 | 6500 | 0.7780 | 0.6917 |
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+ | 0.6268 | 7.02 | 7000 | 0.7905 | 0.6893 |
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+ | 0.619 | 7.52 | 7500 | 0.7644 | 0.6991 |
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+ | 0.6008 | 8.02 | 8000 | 0.7473 | 0.7086 |
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+ | 0.5824 | 8.53 | 8500 | 0.7601 | 0.7009 |
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+ | 0.5687 | 9.03 | 9000 | 0.7795 | 0.6888 |
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+ | 0.5466 | 9.53 | 9500 | 0.7925 | 0.7045 |
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  ### Framework versions
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+ - Transformers 4.33.0
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  - Pytorch 2.0.1+cu118
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  - Datasets 2.14.4
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  - Tokenizers 0.13.3
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