---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: multibert_seed37_1311
  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. -->

# multibert_seed37_1311

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: 0.3744
- Precisions: 0.8548
- Recall: 0.8200
- F-measure: 0.8358
- Accuracy: 0.9371

## 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: 7.5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 37
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 14

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.4464        | 1.0   | 236  | 0.2769          | 0.8836     | 0.7193 | 0.7495    | 0.9197   |
| 0.2278        | 2.0   | 472  | 0.2576          | 0.8850     | 0.7524 | 0.7965    | 0.9296   |
| 0.1314        | 3.0   | 708  | 0.3066          | 0.8740     | 0.7725 | 0.8059    | 0.9284   |
| 0.0964        | 4.0   | 944  | 0.3072          | 0.8267     | 0.7989 | 0.8054    | 0.9311   |
| 0.0612        | 5.0   | 1180 | 0.3229          | 0.8601     | 0.8044 | 0.8297    | 0.9340   |
| 0.0446        | 6.0   | 1416 | 0.3647          | 0.8433     | 0.7686 | 0.7952    | 0.9320   |
| 0.0319        | 7.0   | 1652 | 0.3744          | 0.8548     | 0.8200 | 0.8358    | 0.9371   |
| 0.0192        | 8.0   | 1888 | 0.4170          | 0.8724     | 0.7854 | 0.8176    | 0.9359   |
| 0.0132        | 9.0   | 2124 | 0.3994          | 0.8723     | 0.7887 | 0.8178    | 0.9371   |
| 0.0099        | 10.0  | 2360 | 0.4482          | 0.8750     | 0.8026 | 0.8327    | 0.9373   |
| 0.005         | 11.0  | 2596 | 0.4510          | 0.8731     | 0.7887 | 0.8244    | 0.9371   |
| 0.0024        | 12.0  | 2832 | 0.4455          | 0.8543     | 0.7969 | 0.8210    | 0.9373   |
| 0.0016        | 13.0  | 3068 | 0.4603          | 0.8742     | 0.8062 | 0.8355    | 0.9395   |
| 0.0018        | 14.0  | 3304 | 0.4660          | 0.8729     | 0.7996 | 0.8306    | 0.9393   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1