---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 618a4f2bfaf95c80657fe91852b9933f
  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. -->

# 618a4f2bfaf95c80657fe91852b9933f

This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the contemmcm/cls_20newsgroups dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4856
- Data Size: 1.0
- Epoch Runtime: 30.6639
- Accuracy: 0.8818
- F1 Macro: 0.8820

## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Data Size | Epoch Runtime | Accuracy | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------------:|:--------:|:--------:|
| No log        | 0     | 0    | 3.0123          | 0         | 2.2889        | 0.0512   | 0.0058   |
| No log        | 1     | 499  | 3.0103          | 0.0078    | 2.9290        | 0.0476   | 0.0142   |
| 0.0305        | 2     | 998  | 2.9595          | 0.0156    | 2.9063        | 0.0585   | 0.0220   |
| 0.0536        | 3     | 1497 | 2.3570          | 0.0312    | 3.5234        | 0.2898   | 0.1913   |
| 0.0887        | 4     | 1996 | 1.6419          | 0.0625    | 4.4454        | 0.5055   | 0.4374   |
| 1.42          | 5     | 2495 | 1.1262          | 0.125     | 6.4097        | 0.6532   | 0.6168   |
| 0.8556        | 6     | 2994 | 0.8115          | 0.25      | 9.8103        | 0.7364   | 0.7160   |
| 0.685         | 7     | 3493 | 0.6446          | 0.5       | 16.8619       | 0.8029   | 0.8043   |
| 0.489         | 8.0   | 3992 | 0.4472          | 1.0       | 32.0749       | 0.8619   | 0.8597   |
| 0.3862        | 9.0   | 4491 | 0.4321          | 1.0       | 30.4782       | 0.8695   | 0.8695   |
| 0.2226        | 10.0  | 4990 | 0.4587          | 1.0       | 30.8529       | 0.8687   | 0.8662   |
| 0.1968        | 11.0  | 5489 | 0.4383          | 1.0       | 31.5420       | 0.8808   | 0.8792   |
| 0.1869        | 12.0  | 5988 | 0.4795          | 1.0       | 30.1504       | 0.8858   | 0.8843   |
| 0.1479        | 13.0  | 6487 | 0.4856          | 1.0       | 30.6639       | 0.8818   | 0.8820   |


### Framework versions

- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.3.0
- Tokenizers 0.22.1