---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: Full-8epoch-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-8epoch-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: 0.0772
- Accuracy: 0.3055
- Precision: 0.5539
- Recall: 0.8444
- F1: 0.5463

## 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: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.1609        | 1.0   | 1563  | 0.1237          | 0.3003   | 0.5394    | 0.8062 | 0.5257 |
| 0.1031        | 2.0   | 3126  | 0.0926          | 0.3033   | 0.5628    | 0.8280 | 0.5475 |
| 0.0805        | 3.0   | 4689  | 0.0831          | 0.3043   | 0.5396    | 0.8360 | 0.5317 |
| 0.0687        | 4.0   | 6252  | 0.0789          | 0.3048   | 0.5514    | 0.8404 | 0.5428 |
| 0.0595        | 5.0   | 7815  | 0.0767          | 0.3051   | 0.5386    | 0.8415 | 0.5347 |
| 0.0529        | 6.0   | 9378  | 0.0770          | 0.3053   | 0.5506    | 0.8425 | 0.5444 |
| 0.048         | 7.0   | 10941 | 0.0765          | 0.3055   | 0.5516    | 0.8444 | 0.5451 |
| 0.0453        | 8.0   | 12504 | 0.0772          | 0.3055   | 0.5539    | 0.8444 | 0.5463 |


### Framework versions

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