---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: multibert_seed35_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_seed35_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: 0.4565
- Precisions: 0.8851
- Recall: 0.8156
- F-measure: 0.8447
- Accuracy: 0.9385

## 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: 35
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.4595        | 1.0   | 236  | 0.2631          | 0.8847     | 0.7209 | 0.7552    | 0.9209   |
| 0.2301        | 2.0   | 472  | 0.2468          | 0.8447     | 0.7729 | 0.7954    | 0.9224   |
| 0.1332        | 3.0   | 708  | 0.2457          | 0.8468     | 0.7925 | 0.8086    | 0.9301   |
| 0.082         | 4.0   | 944  | 0.3261          | 0.8749     | 0.7855 | 0.8184    | 0.9303   |
| 0.0511        | 5.0   | 1180 | 0.3209          | 0.8952     | 0.8048 | 0.8379    | 0.9405   |
| 0.0363        | 6.0   | 1416 | 0.3568          | 0.8594     | 0.8056 | 0.8290    | 0.9337   |
| 0.0214        | 7.0   | 1652 | 0.3562          | 0.8851     | 0.8068 | 0.8350    | 0.9395   |
| 0.0152        | 8.0   | 1888 | 0.4160          | 0.8679     | 0.8065 | 0.8309    | 0.9371   |
| 0.0136        | 9.0   | 2124 | 0.4247          | 0.8732     | 0.8103 | 0.8375    | 0.9342   |
| 0.0096        | 10.0  | 2360 | 0.4242          | 0.8864     | 0.8041 | 0.8381    | 0.9378   |
| 0.0036        | 11.0  | 2596 | 0.4306          | 0.8746     | 0.8122 | 0.8365    | 0.9373   |
| 0.0029        | 12.0  | 2832 | 0.4420          | 0.8744     | 0.8220 | 0.8446    | 0.9385   |
| 0.0014        | 13.0  | 3068 | 0.4526          | 0.8850     | 0.8090 | 0.8395    | 0.9376   |
| 0.002         | 14.0  | 3304 | 0.4565          | 0.8851     | 0.8156 | 0.8447    | 0.9385   |


### Framework versions

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