---
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: []
---

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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: 0.1408
- Precision: 0.5468
- Recall: 0.4523
- F1: 0.4951
- Accuracy: 0.9518

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 71   | 0.1657          | 0.4603    | 0.2935 | 0.3585 | 0.9383   |
| No log        | 2.0   | 142  | 0.1466          | 0.5831    | 0.3838 | 0.4629 | 0.9493   |
| No log        | 3.0   | 213  | 0.1408          | 0.5468    | 0.4523 | 0.4951 | 0.9518   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3