---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: multibert1010_lrate7.5b32
  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. -->

# multibert1010_lrate7.5b32

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: 0.5515
- Precisions: 0.8551
- Recall: 0.8069
- F-measure: 0.8283
- Accuracy: 0.9171

## 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: 32
- eval_batch_size: 32
- seed: 42
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.6054        | 1.0   | 118  | 0.4021          | 0.8661     | 0.6558 | 0.6767    | 0.8698   |
| 0.316         | 2.0   | 236  | 0.4039          | 0.8167     | 0.6935 | 0.7317    | 0.8800   |
| 0.1896        | 3.0   | 354  | 0.3480          | 0.8183     | 0.7792 | 0.7780    | 0.9003   |
| 0.1318        | 4.0   | 472  | 0.3930          | 0.8529     | 0.7703 | 0.7983    | 0.8965   |
| 0.0846        | 5.0   | 590  | 0.4027          | 0.8348     | 0.8010 | 0.8141    | 0.9047   |
| 0.0652        | 6.0   | 708  | 0.4824          | 0.8298     | 0.7555 | 0.7855    | 0.9002   |
| 0.0398        | 7.0   | 826  | 0.5446          | 0.8697     | 0.7766 | 0.8110    | 0.9017   |
| 0.0335        | 8.0   | 944  | 0.4761          | 0.8402     | 0.8013 | 0.8192    | 0.9054   |
| 0.0228        | 9.0   | 1062 | 0.5232          | 0.8547     | 0.7921 | 0.8156    | 0.9085   |
| 0.0181        | 10.0  | 1180 | 0.5477          | 0.8560     | 0.7968 | 0.8226    | 0.9133   |
| 0.0106        | 11.0  | 1298 | 0.5207          | 0.8370     | 0.8050 | 0.8199    | 0.9142   |
| 0.0075        | 12.0  | 1416 | 0.5381          | 0.8469     | 0.8025 | 0.8229    | 0.9156   |
| 0.0038        | 13.0  | 1534 | 0.5573          | 0.8538     | 0.8061 | 0.8269    | 0.9165   |
| 0.0047        | 14.0  | 1652 | 0.5515          | 0.8551     | 0.8069 | 0.8283    | 0.9171   |


### Framework versions

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