---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: Frozen10-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. -->

# Frozen10-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: 0.6268
- Accuracy: 0.3626
- Precision: 0.5124
- Recall: 0.5049
- F1: 0.3803

## 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  | 0.8902          | 0.3136   | 0.4745    | 0.3572 | 0.2465 |
| No log        | 2.0   | 264  | 0.7901          | 0.3298   | 0.4925    | 0.4019 | 0.2886 |
| No log        | 3.0   | 396  | 0.7504          | 0.3365   | 0.5032    | 0.4185 | 0.2998 |
| 0.9069        | 4.0   | 528  | 0.7162          | 0.3434   | 0.5087    | 0.4450 | 0.3169 |
| 0.9069        | 5.0   | 660  | 0.6849          | 0.3498   | 0.4684    | 0.4536 | 0.3356 |
| 0.9069        | 6.0   | 792  | 0.6673          | 0.3537   | 0.5120    | 0.4640 | 0.3451 |
| 0.9069        | 7.0   | 924  | 0.6550          | 0.3562   | 0.4953    | 0.4866 | 0.3562 |
| 0.6585        | 8.0   | 1056 | 0.6505          | 0.3585   | 0.5117    | 0.4886 | 0.3572 |
| 0.6585        | 9.0   | 1188 | 0.6362          | 0.3601   | 0.5067    | 0.4987 | 0.3721 |
| 0.6585        | 10.0  | 1320 | 0.6317          | 0.3615   | 0.5095    | 0.5023 | 0.3773 |
| 0.6585        | 11.0  | 1452 | 0.6282          | 0.3622   | 0.5084    | 0.5052 | 0.3794 |
| 0.5862        | 12.0  | 1584 | 0.6268          | 0.3626   | 0.5124    | 0.5049 | 0.3803 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1