RoBERTaEncoder.Config

Component: RoBERTaEncoder

class RoBERTaEncoder.Config

Bases: RoBERTaEncoderBase.Config

All Attributes (including base classes)

load_path: Optional[str] = None

save_path: Optional[str] = None

freeze: bool = False

shared_module_key: Optional[str] = None

output_dropout: float = 0.4

embedding_dim: int = 768

pooling: PoolingMethod = <PoolingMethod.CLS_TOKEN: 'cls_token'>

export: bool = False

vocab_size: int = 50265

num_encoder_layers: int = 12

num_attention_heads: int = 12

model_path: str = 'manifold://pytext_training/tree/static/models/roberta_base_torch.pt'

is_finetuned: bool = False

Default JSON

{
    "load_path": null,
    "save_path": null,
    "freeze": false,
    "shared_module_key": null,
    "output_dropout": 0.4,
    "embedding_dim": 768,
    "pooling": "cls_token",
    "export": false,
    "vocab_size": 50265,
    "num_encoder_layers": 12,
    "num_attention_heads": 12,
    "model_path": "manifold://pytext_training/tree/static/models/roberta_base_torch.pt",
    "is_finetuned": false
}