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update model card README.md

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  ---
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- language:
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- - en
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  license: mit
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  tags:
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  - generated_from_trainer
@@ -15,13 +13,13 @@ model-index:
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  name: Text Classification
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  type: text-classification
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  dataset:
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- name: GLUE RTE
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  type: glue
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  args: rte
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.7581227436823105
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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
@@ -29,10 +27,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # roberta-base-rte
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- This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the GLUE RTE dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6365
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- - Accuracy: 0.7581
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  ## Model description
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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: 16
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  - eval_batch_size: 8
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  - seed: 42
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 156 | 0.7072 | 0.4729 |
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- | No log | 2.0 | 312 | 0.6958 | 0.5271 |
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- | No log | 3.0 | 468 | 0.6193 | 0.6462 |
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- | 0.6759 | 4.0 | 624 | 0.6046 | 0.7076 |
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- | 0.6759 | 5.0 | 780 | 0.6365 | 0.7581 |
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- | 0.6759 | 6.0 | 936 | 0.8975 | 0.7545 |
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- | 0.3194 | 7.0 | 1092 | 1.2031 | 0.7581 |
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- | 0.3194 | 8.0 | 1248 | 1.2942 | 0.7581 |
 
 
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  ### Framework versions
 
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  ---
 
 
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  license: mit
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  tags:
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  - generated_from_trainer
 
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  name: Text Classification
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  type: text-classification
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  dataset:
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+ name: glue
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  type: glue
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  args: rte
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.7725631768953068
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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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  # roberta-base-rte
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+ This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the glue dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.3534
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+ - Accuracy: 0.7726
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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  - train_batch_size: 16
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  - eval_batch_size: 8
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 156 | 0.7023 | 0.4729 |
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+ | No log | 2.0 | 312 | 0.6356 | 0.6895 |
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+ | No log | 3.0 | 468 | 0.5177 | 0.7617 |
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+ | 0.6131 | 4.0 | 624 | 0.6238 | 0.7473 |
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+ | 0.6131 | 5.0 | 780 | 0.5446 | 0.7978 |
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+ | 0.6131 | 6.0 | 936 | 0.9697 | 0.7545 |
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+ | 0.2528 | 7.0 | 1092 | 1.1004 | 0.7690 |
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+ | 0.2528 | 8.0 | 1248 | 1.1937 | 0.7726 |
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+ | 0.2528 | 9.0 | 1404 | 1.3313 | 0.7726 |
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+ | 0.1073 | 10.0 | 1560 | 1.3534 | 0.7726 |
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  ### Framework versions