Update configuration_ltgbert.py

configuration_ltgbert.py

@@ -1,12 +1,82 @@
+# coding=utf-8
+# Copyright 2023 Language Technology Group from University of Oslo and The HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+""" LTG-BERT configutation """
+
+
 from transformers.configuration_utils import PretrainedConfig
 
 
-class LTGBertConfig(PretrainedConfig):
-    """Configuration class to store the configuration of a `LTGBertModel`.
+LTG_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP = {
+    "bnc-bert-span": "https://huggingface.co/ltg/bnc-bert-span",
+    "bnc-bert-span-2x": "https://huggingface.co/ltg/bnc-bert-span-2x",
+    "bnc-bert-span-0.5x": "https://huggingface.co/ltg/bnc-bert-span-0.5x",
+    "bnc-bert-span-0.25x": "https://huggingface.co/ltg/bnc-bert-span-0.25x",
+    "bnc-bert-span-order": "https://huggingface.co/ltg/bnc-bert-span-order",
+    "bnc-bert-span-document": "https://huggingface.co/ltg/bnc-bert-span-document",
+    "bnc-bert-span-word": "https://huggingface.co/ltg/bnc-bert-span-word",
+    "bnc-bert-span-subword": "https://huggingface.co/ltg/bnc-bert-span-subword",
+
+    "norbert3-xs": "https://huggingface.co/ltg/norbert3-xs/config.json",
+    "norbert3-small": "https://huggingface.co/ltg/norbert3-small/config.json",
+    "norbert3-base": "https://huggingface.co/ltg/norbert3-base/config.json",
+    "norbert3-large": "https://huggingface.co/ltg/norbert3-large/config.json",
+
+    "norbert3-oversampled-base": "https://huggingface.co/ltg/norbert3-oversampled-base/config.json",
+    "norbert3-ncc-base": "https://huggingface.co/ltg/norbert3-ncc-base/config.json",
+    "norbert3-nak-base": "https://huggingface.co/ltg/norbert3-nak-base/config.json",
+    "norbert3-nb-base": "https://huggingface.co/ltg/norbert3-nb-base/config.json",
+    "norbert3-wiki-base": "https://huggingface.co/ltg/norbert3-wiki-base/config.json",
+    "norbert3-c4-base": "https://huggingface.co/ltg/norbert3-c4-base/config.json"
+}
+
+
+class LtgBertConfig(PretrainedConfig):
+    r"""
+    This is the configuration class to store the configuration of a [`LtgBertModel`]. It is used to
+    instantiate an LTG-BERT model according to the specified arguments, defining the model architecture.
+    Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
+    documentation from [`PretrainedConfig`] for more information.
+    Args:
+        vocab_size (`int`, *optional*, defaults to 16384):
+            Vocabulary size of the LTG-BERT model. Defines the number of different tokens that can be represented by the
+            `inputs_ids` passed when calling [`LtgBertModel`].
+        hidden_size (`int`, *optional*, defaults to 768):
+            Dimensionality of the encoder layers and the pooler layer.
+        num_hidden_layers (`int`, *optional*, defaults to 12):
+            Number of hidden layers in the Transformer encoder.
+        num_attention_heads (`int`, *optional*, defaults to 12):
+            Number of attention heads for each attention layer in the Transformer encoder.
+        intermediate_size (`int`, *optional*, defaults to 2048):
+            Dimensionality of the "intermediate" (often named feed-forward) layer in the Transformer encoder.
+        hidden_dropout_prob (`float`, *optional*, defaults to 0.1):
+            The dropout probability for all fully connected layers in the embeddings, encoder, and pooler.
+        attention_probs_dropout_prob (`float`, *optional*, defaults to 0.1):
+            The dropout ratio for the attention probabilities.
+        max_position_embeddings (`int`, *optional*, defaults to 512):
+            The maximum sequence length that this model might ever be used with. Typically set this to something large
+            just in case (e.g., 512 or 1024 or 2048).
+        layer_norm_eps (`float`, *optional*, defaults to 1e-12):
+            The epsilon used by the layer normalization layers.
+        classifier_dropout (`float`, *optional*):
+            The dropout ratio for the classification head.
     """
+    model_type = "bert"
     def __init__(
         self,
-        vocab_size=50000,
+        vocab_size=16384,
         attention_probs_dropout_prob=0.1,
         hidden_dropout_prob=0.1,
         hidden_size=768,
@@ -16,10 +86,12 @@ class LTGBertConfig(PretrainedConfig):
         num_attention_heads=12,
         num_hidden_layers=12,
         layer_norm_eps=1.0e-7,
+        pad_token_id=4,
         output_all_encoded_layers=True,
+        classifier_dropout=None,
         **kwargs,
     ):
-        super().__init__(**kwargs)
+        super().__init__(pad_token_id=pad_token_id, **kwargs)
 
         self.vocab_size = vocab_size
         self.hidden_size = hidden_size
@@ -32,3 +104,4 @@ class LTGBertConfig(PretrainedConfig):
         self.output_all_encoded_layers = output_all_encoded_layers
         self.position_bucket_size = position_bucket_size
         self.layer_norm_eps = layer_norm_eps
+        self.classifier_dropout = classifier_dropout