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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license: mit
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tags:
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- generated_from_trainer
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datasets:
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- glue
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metrics:
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- accuracy
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model-index:
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- name: roberta-base-rte
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results:
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- task:
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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: 0.7581227436823105
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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
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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 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.2942
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- Accuracy: 0.7581
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.06
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- num_epochs: 10.0
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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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| 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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- Transformers 4.20.0.dev0
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- Pytorch 1.11.0+cu113
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- Datasets 2.1.0
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- Tokenizers 0.12.1
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