---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: Full-2epoch-BERT-base-multilingual-finetuned-CEFR_ner-60000news
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Full-2epoch-BERT-base-multilingual-finetuned-CEFR_ner-60000news

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: 0.1113
- Accuracy: 0.3015
- Precision: 0.5856
- Recall: 0.8155
- F1: 0.5650

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.1704        | 1.0   | 1563 | 0.1348          | 0.2991   | 0.5538    | 0.7961 | 0.5345 |
| 0.1196        | 2.0   | 3126 | 0.1113          | 0.3015   | 0.5856    | 0.8155 | 0.5650 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.2.1
- Datasets 2.19.2
- Tokenizers 0.19.1