update model card README.md
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README.md
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---
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language:
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- en
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tags:
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- generated_from_trainer
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datasets:
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name: Text Classification
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type: text-classification
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dataset:
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name:
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type: glue
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config: sst2
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split: validation
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# add_BERT_no_pretrain_sst2
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This model is a fine-tuned version of [](https://huggingface.co/) on the
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy: 0.5092
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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- train_batch_size: 128
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- eval_batch_size: 128
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- seed: 10
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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: 50
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- mixed_precision_training: Native AMP
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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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### Framework versions
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- Transformers 4.
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- Pytorch 1.14.0a0+410ce96
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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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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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: sst2
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split: validation
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# add_BERT_no_pretrain_sst2
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This model is a fine-tuned version of [](https://huggingface.co/) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7002
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- Accuracy: 0.5092
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 4e-05
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- train_batch_size: 128
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- eval_batch_size: 128
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- seed: 10
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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: 50
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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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| 0.6983 | 1.0 | 527 | 0.6936 | 0.5092 |
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| 0.6895 | 2.0 | 1054 | 0.7089 | 0.5092 |
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| 0.6881 | 3.0 | 1581 | 0.6993 | 0.5092 |
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| 0.6875 | 4.0 | 2108 | 0.6994 | 0.5092 |
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| 0.6874 | 5.0 | 2635 | 0.6941 | 0.5092 |
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| 0.687 | 6.0 | 3162 | 0.7002 | 0.5092 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 1.14.0a0+410ce96
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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