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--- |
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license: apache-2.0 |
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base_model: bert-base-uncased |
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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: bert-base-uncased-finetuned-CLS-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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config: rte |
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split: validation |
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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: 0.6967509025270758 |
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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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# bert-base-uncased-finetuned-CLS-RTE |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the glue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2843 |
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- Accuracy: 0.6968 |
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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: 15 |
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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 | 0.6285 | 0.6390 | |
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| No log | 2.0 | 312 | 0.6483 | 0.6679 | |
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| No log | 3.0 | 468 | 0.8430 | 0.7004 | |
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| 0.4504 | 4.0 | 624 | 1.2886 | 0.6606 | |
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| 0.4504 | 5.0 | 780 | 1.6445 | 0.7004 | |
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| 0.4504 | 6.0 | 936 | 1.8099 | 0.6751 | |
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| 0.0631 | 7.0 | 1092 | 1.8173 | 0.7040 | |
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| 0.0631 | 8.0 | 1248 | 1.9799 | 0.7004 | |
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| 0.0631 | 9.0 | 1404 | 1.9767 | 0.6968 | |
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| 0.0159 | 10.0 | 1560 | 2.1696 | 0.6715 | |
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| 0.0159 | 11.0 | 1716 | 2.2142 | 0.6859 | |
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| 0.0159 | 12.0 | 1872 | 2.2605 | 0.6823 | |
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| 0.0076 | 13.0 | 2028 | 2.2775 | 0.7040 | |
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| 0.0076 | 14.0 | 2184 | 2.2719 | 0.6968 | |
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| 0.0076 | 15.0 | 2340 | 2.2843 | 0.6968 | |
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### Framework versions |
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- Transformers 4.36.1 |
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- Pytorch 2.1.2 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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