Upload 8 files
Browse files- README.md +155 -0
- config.json +49 -0
- gitattributes +16 -0
- merges.txt +0 -0
- special_tokens_map.json +1 -0
- tokenizer.json +0 -0
- tokenizer_config.json +1 -0
- vocab.json +0 -0
README.md
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---
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license: apache-2.0
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tags:
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- token-classification
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datasets:
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- conll2003
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: distilroberta-base-ner-conll2003
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results:
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- task:
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type: token-classification
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name: Token Classification
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dataset:
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name: conll2003
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type: conll2003
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metrics:
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- type: precision
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value: 0.9492923423001218
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name: Precision
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- type: recall
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value: 0.9565545901020023
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name: Recall
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- type: f1
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value: 0.9529096297690173
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name: F1
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- type: accuracy
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value: 0.9883096560400111
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name: Accuracy
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- task:
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type: token-classification
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name: Token Classification
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dataset:
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name: conll2003
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type: conll2003
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config: conll2003
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split: validation
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metrics:
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- type: accuracy
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value: 0.9883249976987512
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name: Accuracy
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verified: true
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verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZTEwNzFlMjk0ZDY4NTg2MGQxMDZkM2IyZjdjNDEwYmNiMWY1MWZiNzg1ZjMyZTlkYzQ0MmVmNTZkMjEyMGQ1YiIsInZlcnNpb24iOjF9.zxapWje7kbauQ5-VDNbY487JB5wkN4XqgaLwoX1cSmNfgpp-MPCjqrocxayb1kImbN8CvzOpU1aSfvRfyd5fAw
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- type: precision
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value: 0.9906910190038265
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name: Precision
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verified: true
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verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMWRjMjYyOGQ2MGMwOGE1ODQyNDU1MzZiNWU4MGUzYWVlNjQ3NDhjZDRlZTE0NDlmMGJjZjliZjU2ZmFiZmZiYyIsInZlcnNpb24iOjF9.G_QY9mDkIkllmWPsgmUoVgs-R9XjfYkdJMS8hcyGM-7NXsbigUgZZnhfD0TjDak62UoEplqwSX5r0S4xKPdxBQ
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- type: recall
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value: 0.9916635820847483
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name: Recall
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verified: true
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verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiODE0MDE5ZWMzNTM5MTA1NTI4YzNhNzI2NzVjODIzZWY0OWE2ODJiN2FiNmVkNGVkMTI2ODZiOGEwNTEzNzk2MCIsInZlcnNpb24iOjF9.zenVqRfs8TrKoiIu_QXQJtHyj3dEH97ZDLxUn_UJ2tdW36hpBflgKCJNBvFFkra7bS4cNRfIkwxxCUMWH1ptBg
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- type: f1
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value: 0.9911770619696786
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name: F1
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verified: true
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+
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZWZjY2NiNjZlNDFiODQ3M2JkOWJjNzRlY2FmNjMwNGFkNzFmNTBkOGQ5YTcyZjUzNjAwNDAxMThiNTE5ZThiNiIsInZlcnNpb24iOjF9.c9aD9hycCS-WBaLUb8NKzIpd2LE6xfJrhg3fL9_832RiMq5gcMs9qtarP3Jbo6WbPs_WThr_v4gn7K4Ti-0-CA
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- type: loss
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value: 0.05638007074594498
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name: loss
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verified: true
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verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNGM3NTQ5ODBhMDcyNjBjMGUxMDgzYjI2NjEwNjM0MjU0MjEzMTRmODA2MjMwZWU1YTQ3OWU2YjUzNTliZTkwMSIsInZlcnNpb24iOjF9.03OwbxrdKm-vg6ia5CBYdEaSCuRbT0pLoEvwpd4NtjydVzo5wzS-pWgY6vH4PlI0ZCTBY0Po0IZSsJulWJttDg
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# distilroberta-base-ner-conll2003
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This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the conll2003 dataset.
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eval F1-Score: **95,29** (CoNLL-03)
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test F1-Score: **90,74** (CoNLL-03)
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eval F1-Score: **95,29** (CoNLL++ / CoNLL-03 corrected)
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test F1-Score: **92,23** (CoNLL++ / CoNLL-03 corrected)
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## Model Usage
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```python
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from transformers import AutoTokenizer, AutoModelForTokenClassification
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from transformers import pipeline
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tokenizer = AutoTokenizer.from_pretrained("philschmid/distilroberta-base-ner-conll2003")
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model = AutoModelForTokenClassification.from_pretrained("philschmid/distilroberta-base-ner-conll2003")
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nlp = pipeline("ner", model=model, tokenizer=tokenizer, grouped_entities=True)
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example = "My name is Philipp and live in Germany"
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nlp(example)
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```
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 4.9902376275441704e-05
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- train_batch_size: 32
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 6.0
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- mixed_precision_training: Native AMP
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### Training results
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#### CoNNL2003
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It achieves the following results on the evaluation set:
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- Loss: 0.0583
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- Precision: 0.9493
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- Recall: 0.9566
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- F1: 0.9529
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- Accuracy: 0.9883
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It achieves the following results on the test set:
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- Loss: 0.2025
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- Precision: 0.8999
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- Recall: 0.915
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- F1: 0.9074
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- Accuracy: 0.9741
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#### CoNNL++ / CoNLL2003 corrected
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It achieves the following results on the evaluation set:
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- Loss: 0.0567
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- Precision: 0.9493
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- Recall: 0.9566
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- F1: 0.9529
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- Accuracy: 0.9883
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It achieves the following results on the test set:
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- Loss: 0.1359
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- Precision: 0.92
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- Recall: 0.9245
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- F1: 0.9223
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- Accuracy: 0.9785
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### Framework versions
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- Transformers 4.6.1
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- Pytorch 1.8.1+cu101
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- Datasets 1.6.2
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- Tokenizers 0.10.2
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config.json
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{
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"_name_or_path": "distilroberta-base",
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"architectures": [
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"RobertaForTokenClassification"
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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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"eos_token_id": 2,
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"finetuning_task": "ner",
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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": 768,
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"id2label": {
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"0": "O",
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"1": "B-PER",
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"2": "I-PER",
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"3": "B-ORG",
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"4": "I-ORG",
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"5": "B-LOC",
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"6": "I-LOC",
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"7": "B-MISC",
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"8": "I-MISC"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"O": 0,
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"B-PER": 1,
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"I-PER": 2,
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"B-ORG": 3,
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"I-ORG": 4,
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"B-LOC": 5,
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"I-LOC": 6,
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"B-MISC": 7,
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"I-MISC": 8
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},
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 514,
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"model_type": "roberta",
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"num_attention_heads": 12,
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"num_hidden_layers": 6,
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"transformers_version": "4.6.1",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 50265
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}
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gitattributes
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*.bin.* filter=lfs diff=lfs merge=lfs -text
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*.lfs.* filter=lfs diff=lfs merge=lfs -text
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*.bin filter=lfs diff=lfs merge=lfs -text
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*.h5 filter=lfs diff=lfs merge=lfs -text
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*.tflite filter=lfs diff=lfs merge=lfs -text
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*.tar.gz filter=lfs diff=lfs merge=lfs -text
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*.ot filter=lfs diff=lfs merge=lfs -text
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*.onnx filter=lfs diff=lfs merge=lfs -text
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*.arrow filter=lfs diff=lfs merge=lfs -text
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*.ftz filter=lfs diff=lfs merge=lfs -text
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*.joblib filter=lfs diff=lfs merge=lfs -text
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*.model filter=lfs diff=lfs merge=lfs -text
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*.msgpack filter=lfs diff=lfs merge=lfs -text
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*.pb filter=lfs diff=lfs merge=lfs -text
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*.pt filter=lfs diff=lfs merge=lfs -text
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*.pth filter=lfs diff=lfs merge=lfs -text
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merges.txt
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special_tokens_map.json
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{"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "</s>", "pad_token": "<pad>", "cls_token": "<s>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": false}}
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tokenizer.json
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tokenizer_config.json
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{"unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>", "add_prefix_space": true, "errors": "replace", "sep_token": "</s>", "cls_token": "<s>", "pad_token": "<pad>", "mask_token": "<mask>", "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "distilroberta-base"}
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vocab.json
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