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--- |
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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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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: bert-base-multilingual-cased-finetuned-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-multilingual-cased-finetuned-ner |
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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: 0.2939 |
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- Accuracy: 0.4501 |
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- Precision: 0.5440 |
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- Recall: 0.6659 |
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- F1: 0.4954 |
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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: 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: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| No log | 1.0 | 50 | 0.5390 | 0.3903 | 0.5183 | 0.4448 | 0.3118 | |
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| No log | 2.0 | 100 | 0.4150 | 0.4152 | 0.5575 | 0.5062 | 0.3632 | |
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| No log | 3.0 | 150 | 0.3530 | 0.4289 | 0.5842 | 0.5557 | 0.3945 | |
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| No log | 4.0 | 200 | 0.3272 | 0.4348 | 0.5319 | 0.5761 | 0.4145 | |
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| No log | 5.0 | 250 | 0.3047 | 0.4401 | 0.5175 | 0.6018 | 0.4284 | |
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| No log | 6.0 | 300 | 0.2964 | 0.4422 | 0.5224 | 0.6224 | 0.4600 | |
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| No log | 7.0 | 350 | 0.2927 | 0.4445 | 0.5391 | 0.6302 | 0.4691 | |
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| No log | 8.0 | 400 | 0.2896 | 0.4457 | 0.5295 | 0.6335 | 0.4668 | |
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| No log | 9.0 | 450 | 0.2810 | 0.4482 | 0.5360 | 0.6535 | 0.4846 | |
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| 0.324 | 10.0 | 500 | 0.2852 | 0.4486 | 0.5383 | 0.6554 | 0.4847 | |
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| 0.324 | 11.0 | 550 | 0.2949 | 0.4482 | 0.5372 | 0.6560 | 0.4858 | |
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| 0.324 | 12.0 | 600 | 0.2938 | 0.4494 | 0.5437 | 0.6603 | 0.4917 | |
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| 0.324 | 13.0 | 650 | 0.2906 | 0.4503 | 0.5437 | 0.6664 | 0.4952 | |
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| 0.324 | 14.0 | 700 | 0.2963 | 0.4499 | 0.5466 | 0.6641 | 0.4957 | |
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| 0.324 | 15.0 | 750 | 0.2939 | 0.4501 | 0.5440 | 0.6659 | 0.4954 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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