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README.md
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---
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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-finetuned-sst2
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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: sst2
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.944954128440367
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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-finetuned-sst2
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This model was trained from scratch on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3000
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- Accuracy: 0.9450
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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: 16
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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: 5
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### Training results
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| Training Loss | Epoch | Step | Accuracy | Validation Loss |
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|:-------------:|:-----:|:-----:|:--------:|:---------------:|
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| 0.1106 | 1.0 | 4210 | 0.9255 | 0.3326 |
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| 0.1497 | 2.0 | 8420 | 0.9369 | 0.2858 |
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| 0.1028 | 3.0 | 12630 | 0.3128 | 0.9335 |
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| 0.0872 | 4.0 | 16840 | 0.3000 | 0.9450 |
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| 0.0571 | 5.0 | 21050 | 0.3378 | 0.9427 |
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### Framework versions
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- Transformers 4.11.3
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- Pytorch 1.9.0+cu111
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- Datasets 1.14.0
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- Tokenizers 0.10.3
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