aifeducation (version 1.1.2)

BaseModelBert: BERT-Transformer

Description

Represents models based on BERT.

Value

Does return a new object of this class.

Super classes

aifeducation::AIFEMaster -> aifeducation::AIFEBaseModel -> aifeducation::BaseModelCore -> BaseModelBert

Methods

Public methods

• BaseModelBert$configure()

• BaseModelBert$clone()

Inherited methods

• aifeducation::AIFEMaster$get_all_fields()
• aifeducation::AIFEMaster$get_documentation_license()
• aifeducation::AIFEMaster$get_ml_framework()
• aifeducation::AIFEMaster$get_model_config()
• aifeducation::AIFEMaster$get_model_description()
• aifeducation::AIFEMaster$get_model_info()
• aifeducation::AIFEMaster$get_model_license()
• aifeducation::AIFEMaster$get_package_versions()
• aifeducation::AIFEMaster$get_private()
• aifeducation::AIFEMaster$get_publication_info()
• aifeducation::AIFEMaster$get_sustainability_data()
• aifeducation::AIFEMaster$is_configured()
• aifeducation::AIFEMaster$is_trained()
• aifeducation::AIFEMaster$set_documentation_license()
• aifeducation::AIFEMaster$set_model_description()
• aifeducation::AIFEMaster$set_model_license()
• aifeducation::BaseModelCore$calc_flops_architecture_based()
• aifeducation::BaseModelCore$count_parameter()
• aifeducation::BaseModelCore$create_from_hf()
• aifeducation::BaseModelCore$estimate_sustainability_inference_fill_mask()
• aifeducation::BaseModelCore$fill_mask()
• aifeducation::BaseModelCore$get_final_size()
• aifeducation::BaseModelCore$get_flops_estimates()
• aifeducation::BaseModelCore$get_model()
• aifeducation::BaseModelCore$get_model_type()
• aifeducation::BaseModelCore$get_special_tokens()
• aifeducation::BaseModelCore$get_tokenizer_statistics()
• aifeducation::BaseModelCore$load_from_disk()
• aifeducation::BaseModelCore$plot_training_history()
• aifeducation::BaseModelCore$save()
• aifeducation::BaseModelCore$set_publication_info()
• aifeducation::BaseModelCore$train()

---

Method configure()

Configures a new object of this class.

Usage

BaseModelBert$configure(
  tokenizer,
  max_position_embeddings = 512L,
  hidden_size = 768L,
  num_hidden_layers = 12L,
  num_attention_heads = 12L,
  intermediate_size = 3072L,
  hidden_act = "GELU",
  hidden_dropout_prob = 0.1,
  attention_probs_dropout_prob = 0.1
)

Arguments

tokenizer

TokenizerBase Tokenizer for the model.

max_position_embeddings

int Number of maximum position embeddings. This parameter also determines the maximum length of a sequence which can be processed with the model. Allowed values: 10 <= x <= 4048

hidden_size

int Number of neurons in each layer. This parameter determines the dimensionality of the resulting text embedding. Allowed values: 1 <= x <= 2048

num_hidden_layers

int Number of hidden layers. Allowed values: 1 <= x

num_attention_heads

int determining the number of attention heads for a self-attention layer. Only relevant if attention_type='multihead' Allowed values: 0 <= x

intermediate_size

int determining the size of the projection layer within a each transformer encoder. Allowed values: 1 <= x

hidden_act

string Name of the activation function. Allowed values: 'GELU', 'relu', 'silu', 'gelu_new'

hidden_dropout_prob

double Ratio of dropout. Allowed values: 0 <= x <= 0.6

attention_probs_dropout_prob

double Ratio of dropout for attention probabilities. Allowed values: 0 <= x <= 0.6

Returns

Does nothing return.

---

Method clone()

The objects of this class are cloneable with this method.

Usage

BaseModelBert$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

References

Devlin, J., Chang, M.‑W., Lee, K., & Toutanova, K. (2019). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In J. Burstein, C. Doran, & T. Solorio (Eds.), Proceedings of the 2019 Conference of the North (pp. 4171--4186). Association for Computational Linguistics. tools:::Rd_expr_doi("10.18653/v1/N19-1423")

See Also

Other Base Model: BaseModelDebertaV2, BaseModelFunnel, BaseModelMPNet, BaseModelModernBert, BaseModelRoberta