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edwardyeung04
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my_openbookqa_model

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  1. README.md +12 -12
  2. model.safetensors +1 -1
README.md CHANGED
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  ---
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  license: mit
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- base_model: xlnet-base-cased
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  tags:
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  - generated_from_trainer
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  metrics:
@@ -15,10 +15,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # my_openbookqa_model
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- This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.8070
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- - Accuracy: 0.556
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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: 5e-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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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 310 | 1.2003 | 0.518 |
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- | 1.117 | 2.0 | 620 | 1.1111 | 0.566 |
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- | 1.117 | 3.0 | 930 | 1.3611 | 0.564 |
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- | 0.6722 | 4.0 | 1240 | 1.6125 | 0.566 |
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- | 0.3474 | 5.0 | 1550 | 1.8070 | 0.556 |
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  ### Framework versions
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- - Transformers 4.35.2
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  - Pytorch 2.1.0+cu121
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- - Datasets 2.17.0
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  - Tokenizers 0.15.2
 
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  ---
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  license: mit
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+ base_model: microsoft/deberta-v3-large
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  # my_openbookqa_model
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+ This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.3087
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+ - Accuracy: 0.8
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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: 3e-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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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 310 | 0.6199 | 0.772 |
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+ | 0.558 | 2.0 | 620 | 0.8981 | 0.774 |
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+ | 0.558 | 3.0 | 930 | 1.0692 | 0.774 |
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+ | 0.1038 | 4.0 | 1240 | 1.2853 | 0.8 |
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+ | 0.0205 | 5.0 | 1550 | 1.3087 | 0.8 |
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  ### Framework versions
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+ - Transformers 4.38.1
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  - Pytorch 2.1.0+cu121
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+ - Datasets 2.18.0
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  - Tokenizers 0.15.2
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