vinucmer-small / tokenizer_config.json
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training roberta structure with 4808259 samples, 2406 test samples, 500 vocab size, 3 hidden layers, 256 hidden size, 4 attention heads, 0.15 mlm probability, 10 num process, 512 max length, 0.0005 train test split, 50 min sub seq length, 2000 max sub seq length, 42 seed
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{
"added_tokens_decoder": {
"0": {
"content": "<UNK>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"1": {
"content": "<SEP>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"2": {
"content": "<MASK>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"3": {
"content": "<CLS>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"4": {
"content": "<PAD>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
}
},
"clean_up_tokenization_spaces": true,
"cls_token": "<CLS>",
"mask_token": "<MASK>",
"max_length": 512,
"model_max_length": 512,
"pad_token": "<PAD>",
"sep_token": "<SEP>",
"stride": 0,
"tokenizer_class": "PreTrainedTokenizerFast",
"truncation_side": "right",
"truncation_strategy": "longest_first",
"unk_token": "<UNK>"
}