---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: Frozen10-8epoch-BERT-multilingual-finetuned-CEFR_ner-3000news
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Frozen10-8epoch-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: 0.6817
- Accuracy: 0.3506
- Precision: 0.5220
- Recall: 0.4650
- F1: 0.3491

## 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  | 0.8923          | 0.3134   | 0.4780    | 0.3506 | 0.2419 |
| No log        | 2.0   | 264  | 0.7952          | 0.3291   | 0.5018    | 0.4007 | 0.2921 |
| No log        | 3.0   | 396  | 0.7565          | 0.3354   | 0.5125    | 0.4119 | 0.2994 |
| 0.9121        | 4.0   | 528  | 0.7263          | 0.3417   | 0.5153    | 0.4392 | 0.3192 |
| 0.9121        | 5.0   | 660  | 0.7022          | 0.3463   | 0.5347    | 0.4435 | 0.3325 |
| 0.9121        | 6.0   | 792  | 0.6906          | 0.3482   | 0.5347    | 0.4519 | 0.3394 |
| 0.9121        | 7.0   | 924  | 0.6828          | 0.3503   | 0.5218    | 0.4655 | 0.3497 |
| 0.69          | 8.0   | 1056 | 0.6817          | 0.3506   | 0.5220    | 0.4650 | 0.3491 |


### Framework versions

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