---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: sdg-bert-base-multilingual-cased-classification
  results:
  - task:
      type: text-classification
      name: text-classification
    dataset:
      name: albertmartinez/OSDG
      type: albertmartinez/OSDG
      split: test
    metrics:
    - type: accuracy
      value: 0.7982568274259152
      name: accuracy
      args:
        accuracy: 0.7982568274259152
    - type: accuracy
      value: 0.7982568274259152
      name: accuracy
      args:
        accuracy: 0.7982568274259152
        total_time_in_seconds: 41.76398990501184
        samples_per_second: 206.03874341439217
        latency_in_seconds: 0.004853456119118169
    - type: accuracy
      value: 0.7982568274259152
      name: accuracy
      args:
        accuracy: 0.7982568274259152
        total_time_in_seconds: 41.774588764994405
        samples_per_second: 205.9864681950066
        latency_in_seconds: 0.00485468782858738
---

<!-- 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. -->

# sdg-bert-base-multilingual-cased-classification

This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7135
- Accuracy: 0.7981

## 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: 2e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2927        | 1.0   | 269  | 0.8947          | 0.7515   |
| 0.7953        | 2.0   | 538  | 0.7700          | 0.7795   |
| 0.6549        | 3.0   | 807  | 0.7241          | 0.7937   |
| 0.5658        | 4.0   | 1076 | 0.7135          | 0.7984   |
| 0.4799        | 5.0   | 1345 | 0.7142          | 0.7941   |


### Framework versions

- Transformers 4.49.0.dev0
- Pytorch 2.6.0+cu118
- Datasets 2.19.2
- Tokenizers 0.21.0