---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: multibertfinetuned2408
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# multibertfinetuned2408

This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3350
- Precision: 0.7395
- Recall: 0.7408
- F1: 0.7401
- Accuracy: 0.9041

## 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: 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 236  | 0.3641          | 0.6769    | 0.6472 | 0.6617 | 0.8806   |
| No log        | 2.0   | 472  | 0.3733          | 0.7173    | 0.6741 | 0.6950 | 0.8906   |
| 0.429         | 3.0   | 708  | 0.3350          | 0.7395    | 0.7408 | 0.7401 | 0.9041   |
| 0.429         | 4.0   | 944  | 0.4290          | 0.7572    | 0.7279 | 0.7422 | 0.9030   |
| 0.1313        | 5.0   | 1180 | 0.4485          | 0.7432    | 0.7332 | 0.7381 | 0.9007   |
| 0.1313        | 6.0   | 1416 | 0.4799          | 0.7785    | 0.7425 | 0.7601 | 0.9100   |
| 0.0504        | 7.0   | 1652 | 0.5249          | 0.7875    | 0.7461 | 0.7662 | 0.9103   |
| 0.0504        | 8.0   | 1888 | 0.5146          | 0.7863    | 0.7513 | 0.7684 | 0.9120   |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3