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README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: bert-base-multilingual-cased
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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: base_bert_ner_model
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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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# base_bert_ner_model
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This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7122
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- Precision: 0.2260
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- Recall: 0.0256
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- F1: 0.0460
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- Accuracy: 0.8504
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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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 5
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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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| No log | 1.0 | 299 | 0.7522 | 0.1667 | 0.0008 | 0.0015 | 0.8492 |
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| 0.7628 | 2.0 | 598 | 0.7353 | 0.2466 | 0.0140 | 0.0264 | 0.8499 |
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| 0.7628 | 3.0 | 897 | 0.7247 | 0.2273 | 0.0233 | 0.0422 | 0.8509 |
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| 0.7019 | 4.0 | 1196 | 0.7177 | 0.2619 | 0.0256 | 0.0466 | 0.8521 |
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| 0.7019 | 5.0 | 1495 | 0.7122 | 0.2260 | 0.0256 | 0.0460 | 0.8504 |
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### Framework versions
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- Transformers 4.54.0
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- Pytorch 2.6.0+cu124
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- Datasets 4.0.0
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- Tokenizers 0.21.2
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