---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: NLP-HIBA_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-HIBA_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: 0.2057
- Precision: 0.6288
- Recall: 0.5579
- F1: 0.5912
- Accuracy: 0.9555

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 71   | 0.1547          | 0.5048    | 0.3774 | 0.4319 | 0.9430   |
| No log        | 2.0   | 142  | 0.1542          | 0.5965    | 0.4071 | 0.4839 | 0.9495   |
| No log        | 3.0   | 213  | 0.1369          | 0.5519    | 0.5160 | 0.5334 | 0.9516   |
| No log        | 4.0   | 284  | 0.1435          | 0.5622    | 0.4989 | 0.5287 | 0.9512   |
| No log        | 5.0   | 355  | 0.1542          | 0.5920    | 0.5575 | 0.5742 | 0.9536   |
| No log        | 6.0   | 426  | 0.1625          | 0.6069    | 0.5663 | 0.5859 | 0.9546   |
| No log        | 7.0   | 497  | 0.1779          | 0.5936    | 0.5830 | 0.5883 | 0.9526   |
| 0.0978        | 8.0   | 568  | 0.1827          | 0.6035    | 0.5784 | 0.5907 | 0.9546   |
| 0.0978        | 9.0   | 639  | 0.2026          | 0.6121    | 0.5685 | 0.5895 | 0.9546   |
| 0.0978        | 10.0  | 710  | 0.2057          | 0.6288    | 0.5579 | 0.5912 | 0.9555   |


### Framework versions

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