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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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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 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 |
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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 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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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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