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README.md
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This model is a fine-tuned version of [alistvt/bert-base-uncased-pretrained-mlm-coqa-stories](https://huggingface.co/alistvt/bert-base-uncased-pretrained-mlm-coqa-stories) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.
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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: 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:
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### Training results
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| 2.3314 | 2.36 | 16000 | 2.7836 |
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| 2.3433 | 2.65 | 18000 | 2.7650 |
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| 2.3604 | 2.95 | 20000 | 2.7585 |
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### Framework versions
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This model is a fine-tuned version of [alistvt/bert-base-uncased-pretrained-mlm-coqa-stories](https://huggingface.co/alistvt/bert-base-uncased-pretrained-mlm-coqa-stories) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.8125
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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: 1e-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: 4
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### Training results
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| 2.3314 | 2.36 | 16000 | 2.7836 |
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| 2.3433 | 2.65 | 18000 | 2.7650 |
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| 2.3604 | 2.95 | 20000 | 2.7585 |
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| 2.2232 | 3.24 | 22000 | 2.8120 |
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| 2.2094 | 3.53 | 24000 | 2.7945 |
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| 2.2306 | 3.83 | 26000 | 2.8125 |
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### Framework versions
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