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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: Frozen10-8epoch-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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# Frozen10-8epoch-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: 0.6817 |
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- Accuracy: 0.3506 |
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- Precision: 0.5220 |
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- Recall: 0.4650 |
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- F1: 0.3491 |
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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: 8 |
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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 | 0.8923 | 0.3134 | 0.4780 | 0.3506 | 0.2419 | |
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| No log | 2.0 | 264 | 0.7952 | 0.3291 | 0.5018 | 0.4007 | 0.2921 | |
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| No log | 3.0 | 396 | 0.7565 | 0.3354 | 0.5125 | 0.4119 | 0.2994 | |
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| 0.9121 | 4.0 | 528 | 0.7263 | 0.3417 | 0.5153 | 0.4392 | 0.3192 | |
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| 0.9121 | 5.0 | 660 | 0.7022 | 0.3463 | 0.5347 | 0.4435 | 0.3325 | |
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| 0.9121 | 6.0 | 792 | 0.6906 | 0.3482 | 0.5347 | 0.4519 | 0.3394 | |
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| 0.9121 | 7.0 | 924 | 0.6828 | 0.3503 | 0.5218 | 0.4655 | 0.3497 | |
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| 0.69 | 8.0 | 1056 | 0.6817 | 0.3506 | 0.5220 | 0.4650 | 0.3491 | |
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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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