---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: Frozen11-8epoch-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. -->

# Frozen11-8epoch-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: 0.6206
- Accuracy: 0.3654
- Precision: 0.5146
- Recall: 0.5208
- F1: 0.4022

## 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 132  | 0.6667          | 0.3546   | 0.5202    | 0.4775 | 0.3676 |
| No log        | 2.0   | 264  | 0.6564          | 0.3574   | 0.5171    | 0.4956 | 0.3796 |
| No log        | 3.0   | 396  | 0.6472          | 0.3599   | 0.5112    | 0.4998 | 0.3840 |
| 0.6062        | 4.0   | 528  | 0.6354          | 0.3622   | 0.5107    | 0.5109 | 0.3927 |
| 0.6062        | 5.0   | 660  | 0.6282          | 0.3641   | 0.5198    | 0.5115 | 0.3962 |
| 0.6062        | 6.0   | 792  | 0.6254          | 0.3647   | 0.5192    | 0.5176 | 0.3988 |
| 0.6062        | 7.0   | 924  | 0.6212          | 0.3653   | 0.5156    | 0.5224 | 0.4040 |
| 0.5499        | 8.0   | 1056 | 0.6206          | 0.3654   | 0.5146    | 0.5208 | 0.4022 |


### Framework versions

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