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Model save

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Files changed (5) hide show
  1. README.md +8 -23
  2. config.json +27 -19
  3. model.safetensors +2 -2
  4. tokenizer.json +6 -1
  5. training_args.bin +2 -2
README.md CHANGED
@@ -1,13 +1,8 @@
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  ---
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  license: mit
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- base_model: surrey-nlp/roberta-base-finetuned-abbr
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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: bert-base-NER-finetuned-ner
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  results: []
@@ -18,13 +13,7 @@ should probably proofread and complete it, then remove this comment. -->
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  # bert-base-NER-finetuned-ner
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- This model is a fine-tuned version of [surrey-nlp/roberta-base-finetuned-abbr](https://huggingface.co/surrey-nlp/roberta-base-finetuned-abbr) on an unknown dataset.
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- It achieves the following results on the evaluation set:
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- - Loss: 0.4944
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- - Precision: 0.8197
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- - Recall: 0.8510
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- - F1: 0.8350
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- - Accuracy: 0.8172
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  ## Model description
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@@ -44,23 +33,19 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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- - train_batch_size: 8
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  - eval_batch_size: 4
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  - seed: 42
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  - gradient_accumulation_steps: 4
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- - total_train_batch_size: 32
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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: 20
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  - mixed_precision_training: Native AMP
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- ### Training results
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-
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-
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-
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  ### Framework versions
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- - Transformers 4.37.2
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  - Pytorch 2.2.2+cu121
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- - Datasets 2.18.0
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- - Tokenizers 0.15.1
 
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  ---
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  license: mit
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+ base_model: dslim/bert-base-NER
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  tags:
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  - generated_from_trainer
 
 
 
 
 
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  model-index:
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  - name: bert-base-NER-finetuned-ner
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  results: []
 
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  # bert-base-NER-finetuned-ner
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+ This model is a fine-tuned version of [dslim/bert-base-NER](https://huggingface.co/dslim/bert-base-NER) on an unknown dataset.
 
 
 
 
 
 
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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+ - train_batch_size: 4
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  - eval_batch_size: 4
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  - seed: 42
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  - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 16
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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: 5
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  - mixed_precision_training: Native AMP
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  ### Framework versions
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+ - Transformers 4.39.3
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  - Pytorch 2.2.2+cu121
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+ - Datasets 2.19.0
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+ - Tokenizers 0.15.2
config.json CHANGED
@@ -1,41 +1,49 @@
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  {
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- "_name_or_path": "surrey-nlp/roberta-base-finetuned-abbr",
 
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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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  "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-AC",
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- "2": "I-AC",
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- "3": "B-LF",
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- "4": "I-LF"
 
 
 
 
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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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- "B-AC": 1,
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- "B-LF": 3,
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- "I-AC": 2,
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- "I-LF": 4,
 
 
 
 
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  "O": 0
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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": 12,
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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": "4.37.2",
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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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  {
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+ "_name_or_path": "dslim/bert-base-NER",
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  "architectures": [
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  "attention_probs_dropout_prob": 0.1,
 
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  "classifier_dropout": null,
 
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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-MISC",
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+ "2": "I-MISC",
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+ "3": "B-PER",
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+ "4": "I-PER",
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+ "5": "B-ORG",
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  "initializer_range": 0.02,
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  "intermediate_size": 3072,
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  "O": 0
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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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+ "output_past": true,
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  "position_embedding_type": "absolute",
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  "torch_dtype": "float32",
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+ "transformers_version": "4.39.3",
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+ "type_vocab_size": 2,
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  "use_cache": true,
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  }
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