adding model files

README.md

@@ -1,3 +1,44 @@
----
-license: mit
----
+# bert-small-buddhist-nonbuddhist-sanskrit
+
+BERT model trained on a lemmatized corpus containing Buddhist and non-Buddhist Sanskrit texts. 
+
+## Model description
+
+The model has the bert architecture and was pretrained from scratch as a masked language model 
+on the lemmatized Sanskrit corpus. Due to lack of resources and to prevent overfitting, the model is smaller than bert-base, 
+i.e. the number of attention heads and hidden layers have been reduced to 8 and the context has been reduced to 128 tokens. Vocabulary size is 10000 tokens.
+
+## How to use it
+
+```
+model = AutoModelForMaskedLM.from_pretrained("Matej/bert-small-buddhist-nonbuddhist-sanskrit")
+tokenizer = AutoTokenizer.from_pretrained("Matej/bert-small-buddhist-nonbuddhist-sanskrit", use_fast=True)
+```
+
+## Intended uses & limitations
+
+MIT license, no limitations
+
+## Training and evaluation data
+
+See the paper 'Embeddings models for Buddhist Sanskrit' for details on the corpora and the evaluation procedure.
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 32
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 200
+
+### Framework versions
+
+- Transformers 4.20.0
+- Pytorch 1.9.0
+- Datasets 2.3.2
+- Tokenizers 0.12.1
+
+

config.json

@@ -0,0 +1,25 @@
+{
+  "_name_or_path": "configs/models_reference_tokens_all_short_small.json",
+  "architectures": [
+    "BertForMaskedLM"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 128,
+  "model_type": "bert",
+  "num_attention_heads": 8,
+  "num_hidden_layers": 8,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.20.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 10000
+}

pytorch_model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:868f218809024aa909b83949a12ec39dacbf173141e27fd5d3890e40427c559d
+size 260392875

special_tokens_map.json

@@ -0,0 +1,7 @@
+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

@@ -0,0 +1,3 @@
+{
+  "tokenizer_class": "PreTrainedTokenizerFast"
+}