---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: MultiBERTBestModelOct11
  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. -->

# multibert0510_lrate7.5b16

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: 0.5930
- Precisions: 0.8750
- Recall: 0.8217
- F-measure: 0.8450
- Accuracy: 0.9133

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.6022        | 1.0   | 236  | 0.4256          | 0.8484     | 0.6548 | 0.6844    | 0.8642   |
| 0.3396        | 2.0   | 472  | 0.3851          | 0.8046     | 0.7225 | 0.7312    | 0.8773   |
| 0.2116        | 3.0   | 708  | 0.3670          | 0.8311     | 0.7347 | 0.7560    | 0.8947   |
| 0.148         | 4.0   | 944  | 0.4016          | 0.8827     | 0.7716 | 0.8081    | 0.9021   |
| 0.0959        | 5.0   | 1180 | 0.4409          | 0.8338     | 0.8054 | 0.8166    | 0.8998   |
| 0.0809        | 6.0   | 1416 | 0.4964          | 0.8678     | 0.7356 | 0.7799    | 0.8980   |
| 0.056         | 7.0   | 1652 | 0.4894          | 0.8451     | 0.7520 | 0.7855    | 0.8931   |
| 0.038         | 8.0   | 1888 | 0.5008          | 0.8697     | 0.8024 | 0.8301    | 0.9104   |
| 0.031         | 9.0   | 2124 | 0.4813          | 0.8561     | 0.8172 | 0.8335    | 0.9122   |
| 0.02          | 10.0  | 2360 | 0.5857          | 0.8831     | 0.7946 | 0.8305    | 0.9115   |
| 0.0129        | 11.0  | 2596 | 0.5622          | 0.8667     | 0.8039 | 0.8308    | 0.9098   |
| 0.0113        | 12.0  | 2832 | 0.5861          | 0.8746     | 0.8015 | 0.8324    | 0.9104   |
| 0.0065        | 13.0  | 3068 | 0.5964          | 0.8752     | 0.8204 | 0.8443    | 0.9128   |
| 0.004         | 14.0  | 3304 | 0.5930          | 0.8750     | 0.8217 | 0.8450    | 0.9133   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0