---
license: apache-2.0
base_model: distilbert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: NLP-HIBA2_DisTEMIST_fine_tuned_DistilBERT-pretrained-model
  results: []
---

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# NLP-HIBA2_DisTEMIST_fine_tuned_DistilBERT-pretrained-model

This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2224
- Precision: 0.5553
- Recall: 0.5163
- F1: 0.5351
- Accuracy: 0.9502

## 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   | 0.1767          | 0.4612    | 0.4905 | 0.4754 | 0.9399   |
| No log        | 2.0   | 142  | 0.1696          | 0.5173    | 0.4400 | 0.4755 | 0.9481   |
| No log        | 3.0   | 213  | 0.1782          | 0.5189    | 0.5290 | 0.5239 | 0.9485   |
| No log        | 4.0   | 284  | 0.1928          | 0.5275    | 0.4988 | 0.5128 | 0.9475   |
| No log        | 5.0   | 355  | 0.2020          | 0.5800    | 0.4782 | 0.5242 | 0.9512   |
| No log        | 6.0   | 426  | 0.2091          | 0.5645    | 0.4849 | 0.5217 | 0.9506   |
| No log        | 7.0   | 497  | 0.2035          | 0.5608    | 0.5095 | 0.5339 | 0.9511   |
| 0.0531        | 8.0   | 568  | 0.2150          | 0.5282    | 0.5385 | 0.5333 | 0.9484   |
| 0.0531        | 9.0   | 639  | 0.2224          | 0.5639    | 0.5068 | 0.5338 | 0.9507   |
| 0.0531        | 10.0  | 710  | 0.2224          | 0.5553    | 0.5163 | 0.5351 | 0.9502   |


### Framework versions

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