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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: mit
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+ base_model: FacebookAI/xlm-roberta-large
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: xlm-roberta-large_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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+ # xlm-roberta-large_baseline_syllables
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+
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+ This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the covid19_ner dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0838
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+ - Patient Id: 0.9883
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+ - Name: 0.9409
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+ - Gender: 0.9712
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+ - Age: 0.9767
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+ - Job: 0.8506
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+ - Location: 0.9670
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+ - Organization: 0.9134
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+ - Date: 0.9860
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+ - Symptom And Disease: 0.8820
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+ - Transportation: 0.9773
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+ - F1 Macro: 0.9453
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+ - F1 Micro: 0.9587
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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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+ | 0.1707 | 1.0 | 629 | 0.1042 | 0.9528 | 0.9227 | 0.8406 | 0.9523 | 0.5899 | 0.9308 | 0.8045 | 0.9874 | 0.8248 | 0.96 | 0.8766 | 0.9140 |
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+ | 0.0475 | 2.0 | 1258 | 0.0811 | 0.9841 | 0.9372 | 0.9591 | 0.9876 | 0.6849 | 0.9350 | 0.8817 | 0.9847 | 0.8584 | 0.9831 | 0.9196 | 0.9390 |
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+ | 0.0312 | 3.0 | 1887 | 0.0744 | 0.9856 | 0.9297 | 0.9691 | 0.9875 | 0.7554 | 0.9578 | 0.8826 | 0.9869 | 0.8648 | 0.9659 | 0.9285 | 0.9498 |
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+ | 0.0196 | 4.0 | 2516 | 0.0808 | 0.9883 | 0.9465 | 0.9644 | 0.9835 | 0.8346 | 0.9635 | 0.9136 | 0.9856 | 0.8730 | 0.9886 | 0.9442 | 0.9565 |
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+ | 0.0119 | 5.0 | 3145 | 0.0838 | 0.9883 | 0.9409 | 0.9712 | 0.9767 | 0.8506 | 0.9670 | 0.9134 | 0.9860 | 0.8820 | 0.9773 | 0.9453 | 0.9587 |
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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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+ "_name_or_path": "FacebookAI/xlm-roberta-large",
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+ "XLMRobertaForTokenClassification"
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+ ],
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