add model
Browse files- .gitignore +1 -0
- README.md +89 -0
- config.json +46 -0
- pytorch_model.bin +3 -0
- runs/Sep22_10-15-33_949ab5c64c25/1632305750.6199079/events.out.tfevents.1632305750.949ab5c64c25.77.1 +3 -0
- runs/Sep22_10-15-33_949ab5c64c25/events.out.tfevents.1632305750.949ab5c64c25.77.0 +3 -0
- runs/Sep22_10-15-33_949ab5c64c25/events.out.tfevents.1632306283.949ab5c64c25.77.2 +3 -0
- special_tokens_map.json +1 -0
- tokenizer.json +0 -0
- tokenizer_config.json +1 -0
- training_args.bin +3 -0
- vocab.txt +0 -0
.gitignore
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checkpoint-*/
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README.md
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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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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: distilbert-base-uncased-finetuned-ner
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results:
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- task:
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name: Token Classification
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type: token-classification
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dataset:
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name: conll2003
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type: conll2003
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args: conll2003
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metrics:
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- name: Precision
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type: precision
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value: 0.9281908990011098
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- name: Recall
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type: recall
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value: 0.9355632621098557
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- name: F1
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type: f1
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value: 0.9318624993035824
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- name: Accuracy
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type: accuracy
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value: 0.9837641190207635
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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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# distilbert-base-uncased-finetuned-ner
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the conll2003 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0629
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- Precision: 0.9282
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- Recall: 0.9356
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- F1: 0.9319
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- Accuracy: 0.9838
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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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: 2e-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: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.2406 | 1.0 | 878 | 0.0721 | 0.9072 | 0.9172 | 0.9122 | 0.9801 |
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| 0.0529 | 2.0 | 1756 | 0.0637 | 0.9166 | 0.9318 | 0.9241 | 0.9826 |
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| 0.0315 | 3.0 | 2634 | 0.0629 | 0.9282 | 0.9356 | 0.9319 | 0.9838 |
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### Framework versions
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- Transformers 4.10.2
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- Pytorch 1.9.0+cu102
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- Datasets 1.12.1
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- Tokenizers 0.10.3
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config.json
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{
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"_name_or_path": "distilbert-base-uncased",
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"activation": "gelu",
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"architectures": [
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"DistilBertForTokenClassification"
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],
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"attention_dropout": 0.1,
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"dim": 768,
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"dropout": 0.1,
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"hidden_dim": 3072,
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"id2label": {
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"0": "LABEL_0",
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"1": "LABEL_1",
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"2": "LABEL_2",
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"3": "LABEL_3",
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"4": "LABEL_4",
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"5": "LABEL_5",
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"6": "LABEL_6",
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"7": "LABEL_7",
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"8": "LABEL_8"
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},
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"initializer_range": 0.02,
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"label2id": {
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"LABEL_0": 0,
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"LABEL_1": 1,
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"LABEL_2": 2,
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"LABEL_3": 3,
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"LABEL_4": 4,
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"LABEL_5": 5,
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"LABEL_6": 6,
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"LABEL_7": 7,
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"LABEL_8": 8
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},
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"max_position_embeddings": 512,
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"model_type": "distilbert",
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"n_heads": 12,
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"n_layers": 6,
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"pad_token_id": 0,
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"qa_dropout": 0.1,
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"seq_classif_dropout": 0.2,
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"sinusoidal_pos_embds": false,
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"tie_weights_": true,
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"torch_dtype": "float32",
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"transformers_version": "4.10.2",
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"vocab_size": 30522
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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 sha256:153bea2aec0f28bd17a045d2fcc0a485e24723a758932230f958e3a98076d1c2
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size 265518581
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runs/Sep22_10-15-33_949ab5c64c25/1632305750.6199079/events.out.tfevents.1632305750.949ab5c64c25.77.1
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version https://git-lfs.github.com/spec/v1
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oid sha256:8e40f1d3731272a755b986d72d0b989e1077fea23631bf811c53a4c0ca7736b3
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size 4198
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runs/Sep22_10-15-33_949ab5c64c25/events.out.tfevents.1632305750.949ab5c64c25.77.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:3935298ebd27d6ef0230411c690e0af10b3eb48dbac9fbc44850930b1e1e1fa7
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size 5784
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runs/Sep22_10-15-33_949ab5c64c25/events.out.tfevents.1632306283.949ab5c64c25.77.2
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version https://git-lfs.github.com/spec/v1
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oid sha256:38835ec30a006f4580556daf0b0dfa86461741894ef4d9a8da7d9f07fe6ea08a
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size 512
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special_tokens_map.json
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{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}
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tokenizer.json
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tokenizer_config.json
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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, "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "distilbert-base-uncased", "tokenizer_class": "DistilBertTokenizer"}
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:e0b67db46f7252303176ba0940ef7f3705b4f4eaf00ab074712f6ef2e99ab9dd
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size 2671
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vocab.txt
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