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End of training

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README.md ADDED
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+ ---
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+ language:
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+ - vi
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+ license: apache-2.0
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+ base_model: google-bert/bert-base-multilingual-cased
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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-multilingual-cased_baseline_syllables
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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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+ # bert-base-multilingual-cased_baseline_syllables
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+
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+ This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the covid19_ner dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1003
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+ - Patient Id: 0.9860
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+ - Name: 0.9239
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+ - Gender: 0.9642
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+ - Age: 0.9834
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+ - Job: 0.7734
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+ - Location: 0.9494
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+ - Organization: 0.8827
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+ - Date: 0.9883
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+ - Symptom And Disease: 0.8631
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+ - Transportation: 0.9773
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+ - F1 Macro: 0.9292
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+ - F1 Micro: 0.9463
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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: 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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+ - num_epochs: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Patient Id | Name | Gender | Age | Job | Location | Organization | Date | Symptom And Disease | Transportation | F1 Macro | F1 Micro |
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+ |:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:------:|:------:|:------:|:--------:|:------------:|:------:|:-------------------:|:--------------:|:--------:|:--------:|
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+ | 0.1923 | 1.0 | 629 | 0.1099 | 0.9735 | 0.9049 | 0.9288 | 0.9247 | 0.5296 | 0.9225 | 0.7969 | 0.9861 | 0.7873 | 0.9189 | 0.8673 | 0.9102 |
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+ | 0.0555 | 2.0 | 1258 | 0.0937 | 0.9804 | 0.9144 | 0.9586 | 0.9847 | 0.4700 | 0.9390 | 0.8694 | 0.9856 | 0.8604 | 0.9180 | 0.8881 | 0.9353 |
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+ | 0.0334 | 3.0 | 1887 | 0.0875 | 0.9772 | 0.9153 | 0.9590 | 0.9806 | 0.7568 | 0.9450 | 0.8676 | 0.9883 | 0.8571 | 0.96 | 0.9207 | 0.9402 |
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+ | 0.0207 | 4.0 | 2516 | 0.0972 | 0.9859 | 0.9284 | 0.9590 | 0.9808 | 0.7742 | 0.9507 | 0.8919 | 0.9869 | 0.8616 | 0.9718 | 0.9291 | 0.9468 |
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+ | 0.014 | 5.0 | 3145 | 0.1003 | 0.9860 | 0.9239 | 0.9642 | 0.9834 | 0.7734 | 0.9494 | 0.8827 | 0.9883 | 0.8631 | 0.9773 | 0.9292 | 0.9463 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.2
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+ - Pytorch 2.1.2
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+ - Datasets 2.19.2
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+ - Tokenizers 0.19.1
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+ "8": "I-AGE",
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+ "15": "B-DATE",
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+ "20": "I-TRANSPORTATION"
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+ "initializer_range": 0.02,
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+ "num_attention_heads": 12,
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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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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ }
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