model uploaded.
Browse files- README.md +38 -0
- config.json +27 -0
- pytorch_model.bin +3 -0
- tokenizer.json +0 -0
README.md
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---
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license: cc-by-nc-sa-4.0
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---
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---
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language:
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- tr
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tags:
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- roberta
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license: cc-by-nc-sa-4.0
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datasets:
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- oscar
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---
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# RoBERTa Turkish medium WordPiece 7k (uncased)
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Pretrained model on Turkish language using a masked language modeling (MLM) objective. The model is uncased.
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The pretrained corpus is OSCAR's Turkish split, but it is further filtered and cleaned.
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Model architecture is similar to bert-medium (8 layers, 8 heads, and 512 hidden size). Tokenization algorithm is WordPiece. Vocabulary size is 7.5k.
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The details can be found at this paper:
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https://arxiv.org/...
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The following code can be used for model loading and tokenization, example max length (514) can be changed:
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```
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model = AutoModel.from_pretrained([model_path])
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#for sequence classification:
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#model = AutoModelForSequenceClassification.from_pretrained([model_path], num_labels=[num_classes])
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tokenizer = PreTrainedTokenizerFast(tokenizer_file=[file_path])
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tokenizer.mask_token = "[MASK]"
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tokenizer.cls_token = "[CLS]"
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tokenizer.sep_token = "[SEP]"
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tokenizer.pad_token = "[PAD]"
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tokenizer.unk_token = "[UNK]"
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tokenizer.bos_token = "[CLS]"
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tokenizer.eos_token = "[SEP]"
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tokenizer.model_max_length = 514
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```
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### BibTeX entry and citation info
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```bibtex
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@article{}
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```
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config.json
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{
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"architectures": [
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"RobertaForMaskedLM"
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],
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"attention_probs_dropout_prob": 0.1,
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"bos_token_id": 0,
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"classifier_dropout": null,
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"eos_token_id": 2,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 512,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 516,
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"model_type": "roberta",
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"num_attention_heads": 8,
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"num_hidden_layers": 8,
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"torch_dtype": "float32",
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"transformers_version": "4.10.0",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 7500
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:6e5fb8866fb72eea2dec8f397fca3d19d576df4e616144a12cbd0a5d2db2dad9
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size 152025042
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tokenizer.json
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