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: apache-2.0
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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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- f1
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model-index:
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- name: bert-base-uncased-qqp
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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: qqp
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9099925797674994
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- name: F1
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type: f1
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value: 0.8788252139455897
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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-qqp
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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: 0.2829
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- Accuracy: 0.9100
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- F1: 0.8788
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- Combined Score: 0.8944
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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: 32
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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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- num_epochs: 3.0
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
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| 0.2511 | 1.0 | 11371 | 0.2469 | 0.8969 | 0.8641 | 0.8805 |
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| 0.1763 | 2.0 | 22742 | 0.2379 | 0.9071 | 0.8769 | 0.8920 |
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| 0.1221 | 3.0 | 34113 | 0.2829 | 0.9100 | 0.8788 | 0.8944 |
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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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