Zhou Yucheng commited on
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first model version

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README.md CHANGED
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  ---
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  license: apache-2.0
 
 
 
 
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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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: macbert-finetuned-ner-drugname
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+ results: []
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  ---
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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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+
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+ # macbert-finetuned-ner-drugname
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+
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+ This model is a fine-tuned version of [shibing624/macbert4csc-base-chinese](https://huggingface.co/shibing624/macbert4csc-base-chinese) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0195
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+ - Precision: 0.0
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+ - Recall: 0.0
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+ - F1: 0.0
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+ - Accuracy: 0.9971
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 16
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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: 8.0
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:------:|:---------------:|:---------:|:------:|:---:|:--------:|
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+ | 0.0083 | 1.0 | 15362 | 0.0108 | 0.0 | 0.0 | 0.0 | 0.9964 |
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+ | 0.0053 | 2.0 | 30724 | 0.0116 | 0.0 | 0.0 | 0.0 | 0.9963 |
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+ | 0.0037 | 3.0 | 46086 | 0.0091 | 0.0 | 0.0 | 0.0 | 0.9977 |
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+ | 0.0022 | 4.0 | 61448 | 0.0112 | 0.0 | 0.0 | 0.0 | 0.9975 |
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+ | 0.0017 | 5.0 | 76810 | 0.0150 | 0.0 | 0.0 | 0.0 | 0.9970 |
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+ | 0.0008 | 6.0 | 92172 | 0.0175 | 0.0 | 0.0 | 0.0 | 0.9971 |
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+ | 0.0005 | 7.0 | 107534 | 0.0172 | 0.0 | 0.0 | 0.0 | 0.9971 |
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+ | 0.0002 | 8.0 | 122896 | 0.0195 | 0.0 | 0.0 | 0.0 | 0.9971 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.15.0
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+ - Pytorch 1.10.1+cu113
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+ - Datasets 1.17.0
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+ - Tokenizers 0.10.3
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config.json ADDED
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+ {
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+ "_name_or_path": "shibing624/macbert4csc-base-chinese",
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+ "architectures": [
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+ "BertForTokenClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "classifier_dropout": null,
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+ "directionality": "bidi",
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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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+ "2": 2
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 0,
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+ "pooler_fc_size": 768,
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+ "pooler_num_attention_heads": 12,
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+ "pooler_num_fc_layers": 3,
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+ "pooler_size_per_head": 128,
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+ "pooler_type": "first_token_transform",
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+ "position_embedding_type": "absolute",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.15.0",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 21170
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+ }
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tokenizer.json ADDED
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tokenizer_config.json ADDED
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+ {"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "do_basic_tokenize": true, "never_split": null, "name_or_path": "shibing624/macbert4csc-base-chinese", "special_tokens_map_file": "cache\\5559a99a8a2784cef7bf4784ffdb8f0ec2df952f0ca49d9aa3c7f46530fbc8ef.dd8bd9bfd3664b530ea4e645105f557769387b3da9f79bdb55ed556bdd80611d", "tokenizer_class": "BertTokenizer"}
vocab.txt ADDED
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