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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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  metrics:
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  - bleu
 
 
 
 
 
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  model-index:
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  - name: h1
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- results: []
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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-
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  # h1
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- This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.0890
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  - Exact Match: 0.1970
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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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  ---
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  license: apache-2.0
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  tags:
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+ - distigpt2
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+ - hearthstone
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  metrics:
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  - bleu
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+ - dvitel/codebleu
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+ - exact_match
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+ - chrf
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+ datasets:
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+ - dvitel/hearthstone
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  model-index:
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  - name: h1
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+ results:
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+ - task:
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+ type: text-generation
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+ name: Python Code Synthesis
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+ dataset:
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+ type: dvitel/hearthstone
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+ name: HearthStone
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+ split: test
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+ metrics:
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+ - type: exact_match
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+ value: 0.21212121212121213
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+ name: Exact Match
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+ - type: bleu
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+ value: 0.9637468196180485
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+ name: BLEU
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+ - type: dvitel/codebleu
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+ value: 0.8884667222252154
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+ name: CodeBLEU
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+ - type: dvitel/codebleu
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+ value: 96.5942286007928
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+ name: chrF
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  ---
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  # h1
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+ This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on [hearthstone](https://huggingface.co/datasets/dvitel/hearthstone) dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.0890
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  - Exact Match: 0.1970
 
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  ## Model description
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+ DistilGPT2 applied onto HearthStone dataset with preprocessing of python code to dumped AST. Example:
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+ ```python
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+ #gold labels
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+ Module([ClassDef('Innervate', [Name('SpellCard', Load())], [], [FunctionDef('__init__', arguments([], [arg('self', None, None)], None, [], [], None, []), [Expr(Call(Attribute(Call(Name('super', Load()), [], []), '__init__', Load()), [Constant('Innervate', None), Constant(0, None), Attribute(Name('CHARACTER_CLASS', Load()), 'DRUID', Load()), Attribute(Name('CARD_RARITY', Load()), 'FREE', Load())], []))], [], None, None), FunctionDef('use', arguments([], [arg('self', None, None), arg('player', None, None), arg('game', None, None)], None, [], [], None, []), [Expr(Call(Attribute(Call(Name('super', Load()), [], []), 'use', Load()), [Name('player', Load()), Name('game', Load())], [])), If(Compare(Attribute(Name('player', Load()),'mana', Load()), [Lt()], [Constant(8, None)]), [AugAssign(Attribute(Name('player', Load()),'mana', Store()), Add(), Constant(2, None))], [Assign([Attribute(Name('player', Load()),'mana', Store())], Constant(10, None), None)])], [], None, None)], [])], [])
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+ ```
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+ ```python
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+ #wrong prediction (example of error after training)
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+ Module([ClassDef('Innervate', [Name('SpellCard', Load())], [], [FunctionDef('__init__', arguments([], [arg('self', None, None)], None, [], [], None, []), [Expr(Call(Attribute(Call(Name('super', Load()), [], []), '__init__', Load()), [Constant('Innervate', None), Constant(0, None), Attribute(Name('CHARACTER_CLASS', Load()), 'DRUID', Load()), Attribute(Name('CARD_RARITY', Load()), 'FREE', Load())], []))], [], None, None), FunctionDef('use', arguments([], [arg('self', None, None), arg('player', None, None), arg('game', None, None)], None, [], [], None, []), [Expr(Call(Attribute(Call(Name('super', Load()), [], []), 'use', Load()), [Name('player', Load()), Name('game', Load())], [])), For(Compare(Attribute(Name('player', Load()),'maxa', Load()), [Lt()], [Constant(10, None)]), [AugAssign(Attribute(Name('player', Load()),'mana', Store()), Add(), Constant(2, None))], Exign([Name(Name('player', Load()),'mana', Store())], Constant(None, None), None)],], [], None, None)], [])], [])
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+ ```
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+
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  ## Intended uses & limitations
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+ HearthStone card code synthesis.
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  ## Training and evaluation data
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+ See split of [hearthstone](https://huggingface.co/datasets/dvitel/hearthstone) dataset
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  ## Training procedure
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