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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-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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# 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: 0.5691 |
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- Accuracy: 0.4044 |
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- Precision: 0.4949 |
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- Recall: 0.6593 |
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- F1: 0.4688 |
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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 | 0.5657 | 0.3739 | 0.5044 | 0.5333 | 0.4050 | |
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| No log | 2.0 | 264 | 0.5076 | 0.3859 | 0.5011 | 0.5712 | 0.4225 | |
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| No log | 3.0 | 396 | 0.4845 | 0.3925 | 0.4690 | 0.6167 | 0.4351 | |
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| 0.4009 | 4.0 | 528 | 0.4981 | 0.3985 | 0.4956 | 0.6180 | 0.4514 | |
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| 0.4009 | 5.0 | 660 | 0.5136 | 0.3976 | 0.4913 | 0.6348 | 0.4570 | |
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| 0.4009 | 6.0 | 792 | 0.5092 | 0.4019 | 0.5004 | 0.6434 | 0.4655 | |
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| 0.4009 | 7.0 | 924 | 0.5235 | 0.4012 | 0.4837 | 0.6434 | 0.4555 | |
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| 0.1848 | 8.0 | 1056 | 0.5327 | 0.4033 | 0.4948 | 0.6519 | 0.4662 | |
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| 0.1848 | 9.0 | 1188 | 0.5640 | 0.4033 | 0.4920 | 0.6536 | 0.4638 | |
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| 0.1848 | 10.0 | 1320 | 0.5717 | 0.4031 | 0.4962 | 0.6547 | 0.4677 | |
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| 0.1848 | 11.0 | 1452 | 0.5667 | 0.4043 | 0.4910 | 0.6609 | 0.4666 | |
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| 0.1096 | 12.0 | 1584 | 0.5691 | 0.4044 | 0.4949 | 0.6593 | 0.4688 | |
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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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