---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: NLP-CIC-WFU_DisTEMIST_fine_tuned_bert-base-multilingual-cased
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# NLP-CIC-WFU_DisTEMIST_fine_tuned_bert-base-multilingual-cased

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1620
- Precision: 0.6121
- Recall: 0.5161
- F1: 0.5600
- Accuracy: 0.9541

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 71   | 0.1704          | 0.4558    | 0.3635 | 0.4045 | 0.9353   |
| No log        | 2.0   | 142  | 0.1572          | 0.5925    | 0.3518 | 0.4415 | 0.9433   |
| No log        | 3.0   | 213  | 0.1386          | 0.5932    | 0.4774 | 0.5290 | 0.9531   |
| No log        | 4.0   | 284  | 0.1427          | 0.5945    | 0.5175 | 0.5534 | 0.9533   |
| No log        | 5.0   | 355  | 0.1653          | 0.6354    | 0.4788 | 0.5461 | 0.9540   |
| No log        | 6.0   | 426  | 0.1620          | 0.6121    | 0.5161 | 0.5600 | 0.9541   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1