davidliu1110
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End of training
Browse files- .ipynb_checkpoints/README-checkpoint.md +66 -0
- .ipynb_checkpoints/tokenizer_config-checkpoint.json +13 -0
- pytorch_model.bin +1 -1
- tokenizer.json +1 -6
- training_args.bin +1 -1
.ipynb_checkpoints/README-checkpoint.md
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---
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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-chinese-david-ner
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results: []
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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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# bert-base-chinese-david-ner
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This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/bert-base-chinese) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2217
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- Precision: 0.8020
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- Recall: 0.8379
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- F1: 0.8196
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- Accuracy: 0.9471
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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: 8
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- eval_batch_size: 8
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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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- lr_scheduler_warmup_ratio: 0.1
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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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| 0.2487 | 1.4 | 500 | 0.2446 | 0.8138 | 0.8138 | 0.8138 | 0.9417 |
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| 0.0668 | 2.8 | 1000 | 0.2217 | 0.8020 | 0.8379 | 0.8196 | 0.9471 |
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### Framework versions
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- Transformers 4.29.0.dev0
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- Pytorch 1.10.1+cu113
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- Datasets 2.11.0
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- Tokenizers 0.13.3
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.ipynb_checkpoints/tokenizer_config-checkpoint.json
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{
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"clean_up_tokenization_spaces": true,
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"cls_token": "[CLS]",
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"do_lower_case": false,
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "BertTokenizer",
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"unk_token": "[UNK]"
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}
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pytorch_model.bin
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tokenizer.json
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{
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"version": "1.0",
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"truncation":
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"direction": "Right",
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"max_length": 512,
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"strategy": "LongestFirst",
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"stride": 0
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"padding": null,
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"added_tokens": [
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training_args.bin
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