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# bert-base-multilingual-cased-finetuned-lang_class

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0695
- Precision: 0.9145
- Recall: 0.9198
- F1: 0.9172
- Accuracy: 0.9832

## 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: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 233  | 0.0872          | 0.8926    | 0.8930 | 0.8928 | 0.9782   |
| No log        | 2.0   | 466  | 0.0705          | 0.9115    | 0.9182 | 0.9148 | 0.9824   |
| 0.1923        | 3.0   | 699  | 0.0695          | 0.9145    | 0.9198 | 0.9172 | 0.9832   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "bert-base-multilingual-cased", "model-index": [{"name": "bert-base-multilingual-cased-finetuned-lang_class", "results": []}]}
transformers safetensors bert token-classification generated_from_trainer base_model:bert-base-multilingual-cased license:apache-2.0 autotrain_compatible endpoints_compatible region:us