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End of training

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: google-bert/bert-base-multilingual-uncased
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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-multilingual-uncased-finetuned-ner-geocorpus
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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-uncased-finetuned-ner-geocorpus
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+
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+ This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1337
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+ - Precision: 0.7867
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+ - Recall: 0.8827
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+ - F1: 0.8320
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+ - Accuracy: 0.9727
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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: 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: 10
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+
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+ ### Training results
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+
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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 | 276 | 0.1785 | 0.6910 | 0.6597 | 0.6750 | 0.9527 |
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+ | 0.2507 | 2.0 | 552 | 0.1321 | 0.7761 | 0.7689 | 0.7725 | 0.9630 |
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+ | 0.2507 | 3.0 | 828 | 0.1158 | 0.7691 | 0.8165 | 0.7921 | 0.9669 |
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+ | 0.084 | 4.0 | 1104 | 0.1186 | 0.7503 | 0.8479 | 0.7961 | 0.9668 |
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+ | 0.084 | 5.0 | 1380 | 0.1287 | 0.7629 | 0.8560 | 0.8068 | 0.9657 |
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+ | 0.0443 | 6.0 | 1656 | 0.1295 | 0.7453 | 0.8769 | 0.8058 | 0.9666 |
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+ | 0.0443 | 7.0 | 1932 | 0.1423 | 0.7592 | 0.8862 | 0.8178 | 0.9685 |
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+ | 0.0243 | 8.0 | 2208 | 0.1267 | 0.7970 | 0.8664 | 0.8303 | 0.9724 |
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+ | 0.0243 | 9.0 | 2484 | 0.1309 | 0.7747 | 0.8746 | 0.8216 | 0.9710 |
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+ | 0.0164 | 10.0 | 2760 | 0.1337 | 0.7867 | 0.8827 | 0.8320 | 0.9727 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.1
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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