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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: Frozen10-BERT-multilingual-finetuned-CEFR_ner-3000news |
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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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# Frozen10-BERT-multilingual-finetuned-CEFR_ner-3000news |
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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: 0.6268 |
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- Accuracy: 0.3626 |
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- Precision: 0.5124 |
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- Recall: 0.5049 |
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- F1: 0.3803 |
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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: 12 |
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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 | 132 | 0.8902 | 0.3136 | 0.4745 | 0.3572 | 0.2465 | |
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| No log | 2.0 | 264 | 0.7901 | 0.3298 | 0.4925 | 0.4019 | 0.2886 | |
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| No log | 3.0 | 396 | 0.7504 | 0.3365 | 0.5032 | 0.4185 | 0.2998 | |
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| 0.9069 | 4.0 | 528 | 0.7162 | 0.3434 | 0.5087 | 0.4450 | 0.3169 | |
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| 0.9069 | 5.0 | 660 | 0.6849 | 0.3498 | 0.4684 | 0.4536 | 0.3356 | |
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| 0.9069 | 6.0 | 792 | 0.6673 | 0.3537 | 0.5120 | 0.4640 | 0.3451 | |
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| 0.9069 | 7.0 | 924 | 0.6550 | 0.3562 | 0.4953 | 0.4866 | 0.3562 | |
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| 0.6585 | 8.0 | 1056 | 0.6505 | 0.3585 | 0.5117 | 0.4886 | 0.3572 | |
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| 0.6585 | 9.0 | 1188 | 0.6362 | 0.3601 | 0.5067 | 0.4987 | 0.3721 | |
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| 0.6585 | 10.0 | 1320 | 0.6317 | 0.3615 | 0.5095 | 0.5023 | 0.3773 | |
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| 0.6585 | 11.0 | 1452 | 0.6282 | 0.3622 | 0.5084 | 0.5052 | 0.3794 | |
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| 0.5862 | 12.0 | 1584 | 0.6268 | 0.3626 | 0.5124 | 0.5049 | 0.3803 | |
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### Framework versions |
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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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