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---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: BERT-multilingual-finetuned-CEFR_ner-3000news
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# BERT-multilingual-finetuned-CEFR_ner-3000news
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5691
- Accuracy: 0.4044
- Precision: 0.4949
- Recall: 0.6593
- F1: 0.4688
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log | 1.0 | 132 | 0.5657 | 0.3739 | 0.5044 | 0.5333 | 0.4050 |
| No log | 2.0 | 264 | 0.5076 | 0.3859 | 0.5011 | 0.5712 | 0.4225 |
| No log | 3.0 | 396 | 0.4845 | 0.3925 | 0.4690 | 0.6167 | 0.4351 |
| 0.4009 | 4.0 | 528 | 0.4981 | 0.3985 | 0.4956 | 0.6180 | 0.4514 |
| 0.4009 | 5.0 | 660 | 0.5136 | 0.3976 | 0.4913 | 0.6348 | 0.4570 |
| 0.4009 | 6.0 | 792 | 0.5092 | 0.4019 | 0.5004 | 0.6434 | 0.4655 |
| 0.4009 | 7.0 | 924 | 0.5235 | 0.4012 | 0.4837 | 0.6434 | 0.4555 |
| 0.1848 | 8.0 | 1056 | 0.5327 | 0.4033 | 0.4948 | 0.6519 | 0.4662 |
| 0.1848 | 9.0 | 1188 | 0.5640 | 0.4033 | 0.4920 | 0.6536 | 0.4638 |
| 0.1848 | 10.0 | 1320 | 0.5717 | 0.4031 | 0.4962 | 0.6547 | 0.4677 |
| 0.1848 | 11.0 | 1452 | 0.5667 | 0.4043 | 0.4910 | 0.6609 | 0.4666 |
| 0.1096 | 12.0 | 1584 | 0.5691 | 0.4044 | 0.4949 | 0.6593 | 0.4688 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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