---
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
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# 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