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roberta-mc-3

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update model card README.md

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  ---
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- license: mit
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- base_model: roberta-base
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  tags:
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  - generated_from_trainer
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  metrics:
@@ -15,10 +13,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # roberta-mc-3
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- This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.6085
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- - Accuracy: 0.5
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  ## Model description
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@@ -43,22 +41,42 @@ 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: 10
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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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- | 1.6145 | 1.0 | 24 | 1.6087 | 0.3 |
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- | 1.6136 | 2.0 | 48 | 1.6087 | 0.3 |
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- | 1.6076 | 3.0 | 72 | 1.6087 | 0.4 |
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- | 1.6096 | 4.0 | 96 | 1.6087 | 0.4 |
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- | 1.6113 | 5.0 | 120 | 1.6086 | 0.4 |
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- | 1.6097 | 6.0 | 144 | 1.6086 | 0.4 |
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- | 1.6161 | 7.0 | 168 | 1.6086 | 0.4 |
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- | 1.6156 | 8.0 | 192 | 1.6086 | 0.5 |
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- | 1.6127 | 9.0 | 216 | 1.6086 | 0.5 |
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- | 1.6078 | 10.0 | 240 | 1.6085 | 0.5 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  ---
 
 
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  # roberta-mc-3
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+ This model was trained from scratch on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.5988
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+ - Accuracy: 0.3
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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: 30
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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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+ | 1.6111 | 1.0 | 24 | 1.6061 | 0.4 |
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+ | 1.6003 | 2.0 | 48 | 1.6062 | 0.4 |
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+ | 1.6049 | 3.0 | 72 | 1.6062 | 0.4 |
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+ | 1.5936 | 4.0 | 96 | 1.6059 | 0.4 |
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+ | 1.6073 | 5.0 | 120 | 1.6057 | 0.4 |
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+ | 1.6001 | 6.0 | 144 | 1.6055 | 0.3 |
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+ | 1.5925 | 7.0 | 168 | 1.6052 | 0.3 |
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+ | 1.5971 | 8.0 | 192 | 1.6050 | 0.3 |
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+ | 1.597 | 9.0 | 216 | 1.6047 | 0.3 |
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+ | 1.5956 | 10.0 | 240 | 1.6042 | 0.3 |
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+ | 1.5882 | 11.0 | 264 | 1.6036 | 0.3 |
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+ | 1.5944 | 12.0 | 288 | 1.6034 | 0.3 |
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+ | 1.5941 | 13.0 | 312 | 1.6032 | 0.3 |
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+ | 1.5941 | 14.0 | 336 | 1.6029 | 0.3 |
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+ | 1.5825 | 15.0 | 360 | 1.6024 | 0.3 |
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+ | 1.5817 | 16.0 | 384 | 1.6019 | 0.3 |
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+ | 1.5922 | 17.0 | 408 | 1.6014 | 0.3 |
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+ | 1.5915 | 18.0 | 432 | 1.6011 | 0.3 |
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+ | 1.5822 | 19.0 | 456 | 1.6007 | 0.3 |
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+ | 1.5967 | 20.0 | 480 | 1.6001 | 0.3 |
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+ | 1.5887 | 21.0 | 504 | 1.5999 | 0.3 |
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+ | 1.5905 | 22.0 | 528 | 1.5997 | 0.3 |
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+ | 1.5828 | 23.0 | 552 | 1.5994 | 0.3 |
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+ | 1.5851 | 24.0 | 576 | 1.5992 | 0.3 |
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+ | 1.5789 | 25.0 | 600 | 1.5991 | 0.3 |
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+ | 1.5797 | 26.0 | 624 | 1.5990 | 0.3 |
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+ | 1.5845 | 27.0 | 648 | 1.5989 | 0.3 |
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+ | 1.5992 | 28.0 | 672 | 1.5988 | 0.3 |
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+ | 1.5791 | 29.0 | 696 | 1.5988 | 0.3 |
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+ | 1.5785 | 30.0 | 720 | 1.5988 | 0.3 |
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  ### Framework versions