Jeremiah Zhou
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update model card README.md
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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
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name: Text Classification
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type: text-classification
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dataset:
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name:
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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.
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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
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It achieves the following results on the evaluation set:
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- Loss:
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- Accuracy: 0.
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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:
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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.
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| No log | 2.0 | 312 | 0.
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| No log | 3.0 | 468 | 0.
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| 0.
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| 0.
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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
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